Software Engineer, Internal Tools

About SesameAt Sesame, we envision a future where technology transcends mere functionality to become an intuitive part of our daily lives. Our mission is to create lifelike computers capable of perceiving, understanding, and interacting with us in a natural way. We are pioneering a new generation of computing focused on integrating voice agents seamlessly in…

*Candidates must be available for at least 3-5 days per week at one of the following locations:Shackelford, TexasSanta Teresa, New Mexico / (El Paso, TX)Saline, MichiganAbout Our Team:At OpenAI, we are on a transformative journey to establish the most advanced AI infrastructure ecosystem in collaboration with our capital partners. The Stargate team plays a pivotal role in shaping our core infrastructure strategy and executing our ambitious vision. We engage deeply with commercial, technical, strategic, and operational facets, liaising with teams and executives both within and outside of OpenAI.About the Role:We are seeking a dynamic Technical Program Manager who thrives on tackling substantial global challenges with a broad array of stakeholders. This role is integral to the Infrastructure Strategy & Delivery team supporting Stargate, focusing on coordinating datacenter deployments in collaboration with external development and operations teams.Delivering a data center is a complex endeavor that requires a holistic understanding of commercial dependencies, construction timelines, equipment readiness, design specifics, and commissioning timelines. It necessitates a proactive mindset to foresee potential issues and mitigate risks before they arise.In this role, you will be responsible for managing site deployment, ensuring that our data center and supercomputer projects are successfully delivered on schedule. You will work closely with our strategic partners to ensure they meet contractual milestones for AI compute delivery. By fostering relationships, establishing critical timelines, and enhancing supplier performance, you will be at the forefront of OpenAI’s infrastructure and organizational strategy. Infrastructure is destiny, and you will be in the driver's seat!Your Responsibilities:Lead partner performance to meet essential commercial SLAs, construction timelines, and deployment commitments.Act as the primary liaison with external partners for contract alignment, risk management, and high-level reporting.Identify and mitigate risks to datacenter deployments by recognizing critical path items and addressing blockers proactively.Cultivate relationships with internal and external stakeholders, ensuring effective communication and prompt decision-making.

Join Merge Labs, a pioneering research facility dedicated to merging biological and artificial intelligence to enhance human capabilities, agency, and experience. We aim to achieve this by crafting innovative brain-computer interfaces that communicate with the brain at high bandwidth, seamlessly integrate with cutting-edge AI, and prioritize safety and accessibility for all users.About the Team:At Merge Labs, we are on a mission to revolutionize brain-computer interfaces by leveraging advancements in synthetic biology, neuroscience, AI, and non-invasive imaging technologies. Our cross-functional data science team is situated at the convergence of computational modeling, neuroscience, and biomolecular engineering. This collaborative unit works closely with wet-lab scientists, automation specialists, and data engineers to develop machine learning frameworks that facilitate rapid molecule discovery and device enhancement.About the Role:We are seeking a talented Senior / Principal ML Scientist to architect and scale Bayesian optimization and reinforcement learning frameworks that guide molecular engineering initiatives through iterative design-build-test-learn (DBTL) cycles. You will start with a fresh approach to construct the company's closed-loop optimization infrastructure, establishing the data and modeling foundations that link experiments with these ML frameworks. Over time, you will transition prototypes into operational pipelines, significantly enhancing experimental throughput and discovery success across various biomolecular and neuroengineering sectors.Key Responsibilities:Develop the scientific and engineering framework for active learning and closed-loop optimization, encompassing data ingestion, ML modeling, and library design.Collaborate with wet-lab scientists to establish feasible optimization objectives while incorporating domain-specific priors and constraints.Create prototypes for representation learning and acquisition strategies utilizing both internal and public datasets; benchmark and validate the performance of models.Integrate machine learning models with experimental data streams, making them accessible to non-domain experts for broader utilization.Extend machine learning frameworks to accommodate multi-objective or constrained optimization challenges.Stay abreast of the latest advancements in Bayesian optimization, active learning, and reinforcement learning, and prototype innovative algorithms to enhance the company's capabilities.

About UsAt Roboflow, our mission is to empower individuals and organizations to make the world programmable through artificial intelligence. We believe that sight is a fundamental way to understand our surroundings, and we aim to extend this understanding to the software we create and use.We are dedicated to providing the tools, community, and resources necessary for seamless integration of computer vision models. Currently, over 1 million developers, including those from half of the Fortune 100 companies, leverage Roboflow's open-source and hosted machine learning tools. Our applications range from accelerating cancer research through cell counting, enhancing safety at construction sites, digitizing architectural plans, to preserving coral reefs and guiding drone operations.Supported by a robust network of customers and investors, we have raised over $63 million from prominent backers such as Y Combinator, Google Ventures, Craft Ventures, Sam Altman, and Lachy Groom.Our team, known as Roboflowers, consists of passionate builders who value ownership, accountability, and a proactive approach to challenges. We are curious individuals who engage deeply with new technologies, preferring to demonstrate our work rather than simply discuss it. With a founder mindset, we thrive in a high-autonomy environment.Your RoleAs a Technical Support Engineer, you will immerse yourself in a dedicated enterprise customer account, focusing on their specific workflows, edge infrastructure, data pipelines, and operational rhythms. You will build long-lasting, trusted relationships and gain in-depth knowledge of the customer’s environment, representing Roboflow within their organization.Your role will involve both teaching and troubleshooting. You will conduct concise enablement sessions, create customized guides, and develop internal knowledge bases to enhance the customer's computer vision operations.When challenges arise, you will remain calm, structured, and communicative. In quieter times, you will proactively improve processes, gather insights, and strengthen the operational connection between Roboflow and the customer.Your ResponsibilitiesIn your role as the Named Support Engineer, you will:Ensure technical continuity for the customer's computer vision deployment.Develop a comprehensive understanding of their infrastructure, data sources, workflows, and challenges.Act as a trusted advisor, technical guide, and escalation point within the customer’s environment.Lead concise enablement sessions and create tailored documentation to support customer transitions.

About Us Mentis AI operates at the confluence of institutional finance and cutting-edge AI technologies. Our dedicated team merges substantial financial services experience from institutions like Lazard and Partners Group with advanced machine learning and applied AI research. Based in both London and San Francisco, we partner with leading AI research laboratories to enhance model reasoning, generalization, and decision-making in high-stakes financial scenarios.The Opportunity The integration of AI into venture capital workflows is advancing rapidly, from deal sourcing and founder assessment to market evaluation, term sheet negotiation, and portfolio development. This part-time residency offers venture capital professionals the chance to gain practical insights into the construction, evaluation, and enhancement of advanced AI systems within the framework of early and growth-stage investments.Your ResponsibilitiesDevelop Expert Benchmarks: Create and validate real-world investment memoranda, market assessments, and frameworks for evaluating founders that are utilized to assess frontier AI systems.Analyze Model Reasoning: Identify weaknesses in AI-generated venture analyses, pinpointing gaps in logic, assumptions, or investment intuition.Create Evaluation Frameworks: Translate how venture capitalists assess founders, size markets, evaluate competitive landscapes, and build portfolios across various stages and sectors into challenges that test the limits of AI reasoning.Assess Human vs. Machine Judgment: Systematically compare discrepancies between professional venture assessments and AI-generated outputs across deal evaluation, term sheet formulation, and portfolio management environments.Why This Experience MattersBe among the first venture capital professionals to engage directly with how frontier AI models interpret early-stage investing, founder evaluation, and portfolio management.Establish a unique profile for those aiming to merge venture capital with AI, whether in a fund, at an AI startup, or in entrepreneurial ventures.Gain hands-on experience in how AI is transforming venture workflows, from sourcing and due diligence to writing investment memoranda, engaging with boards, and monitoring portfolios.Who You AreA professional with 4+ years of venture capital investing experience at a prestigious VC firm (e.g., Sequoia Capital, Andreessen Horowitz, Accel, Index Ventures).

Shape the Future with AI InnovationAt asari.ai, we are on a mission to empower individuals to create intricate systems and tackle the world's most challenging problems with the aid of advanced AI agents that are both scalable and reliable.Our team boasts a history of publishing award-winning AI research and is supported by elite investors such as Eric Schmidt, Caltech, Jeff Dean, and JP Millon.We thrive in a fast-paced environment, leveraging first-principles thinking and purposeful building. We believe that exceptional outcomes arise when individuals take ownership, grow collectively, and share both the hurdles and victories.Your RoleDesign, train, and assess hybrid AI systems that excel at scale while making optimal trade-offs.Develop scalable data processing and machine learning frameworks.Address min-max challenges: maximizing output while minimizing resources.Enhance our productivity by eliminating operational and tooling constraints.Ideal Candidate ProfileYou find motivation in resolving complex real-world challenges.You possess a proven background in a technical field such as machine learning, computer science, physics, or mathematics.You demonstrate strong programming skills (in Python, C++) and mathematical proficiency.You exhibit robust conceptual and structured thinking abilities.You communicate clearly and effectively, both verbally and in writing.You are eager and capable of rapid learning.You embody a team-oriented spirit.You can independently organize, plan, prioritize, and execute tasks.You are driven by excellence, ownership, and a proactive mindset.Preferred QualificationsExperience with open-source projects, published research, or demonstrated expertise in machine learning.Familiarity with applying deep learning, reinforcement learning, unsupervised learning, and related techniques to large-scale problems.Experience with distributed computing and managing large datasets.Compensation and BenefitsAttractive salaryEquity optionsComprehensive health insurance (100% covered), dental (90% covered), and vision (90% covered). Dependent coverage is at 50%.

Join Our Team as a Senior Applied Scientist!At Gridware, we are on a mission to revolutionize grid management through innovative technology. Based in San Francisco, we are pioneering a cutting-edge approach known as Active Grid Response (AGR). This initiative focuses on enhancing the reliability and safety of the electrical grid by monitoring its electrical, physical, and environmental parameters. Our advanced platform leverages high-precision sensors to identify potential issues early, facilitating proactive maintenance and minimizing outages. Backed by leading climate-tech and Silicon Valley investors, we are poised to make a significant impact in the energy sector. For more insights on our work, visit www.Gridware.io.Role Overview:We are looking for a talented Senior Applied Scientist with a strong background in machine learning and digital signal processing (DSP). In this role, you will be responsible for designing sophisticated models that operate on diverse time-series sensor data within resource-constrained environments. Your work will involve developing algorithms that optimize for accuracy while adhering to strict power and memory constraints, thereby advancing Gridware’s edge intelligence capabilities. This position requires a blend of applied research, model optimization, and close collaboration with hardware and firmware teams to implement low-level solutions.

About Matter IntelligenceWelcome to Matter, a pioneering company at the forefront of vision AI. We are developing an unprecedented sensor capable of perceiving molecular chemistry, temperature, and 3D structure, integrated with a Large World Model that serves as the most advanced intelligence engine for our physical environment. Our unique system not only captures visual data but also comprehends intricate details from a single pixel—what we refer to as Superintelligent Vision.Join a team with an impressive track record, having provided technologies for NASA/JPL's Mars missions, co-founding and spearheading infrastructure for OpenAI, and crafting state-of-the-art sensors for U.S. Defense. Our collective expertise is dedicated to creating the next generation of infrastructure for vision and intelligence in the physical realm.About the RoleWe are in search of a Senior Geospatial Scientist to spearhead the development of sophisticated algorithms and data pipelines that convert our ultraspectral imagery into actionable insights. This pivotal role merges remote sensing science, machine learning, and scalable cloud infrastructure, effectively transforming raw hyperspectral data into validated, production-ready data products.Your responsibilities will include designing and implementing physics-informed machine learning algorithms, constructing robust AWS-based processing pipelines, and ensuring the scientific integrity of each output—from the sensor physics to the final data products. Your contributions will directly empower Matter's mission to deliver transformative Earth observation capabilities across various industries.Key ResponsibilitiesAlgorithm DevelopmentDesign and implement machine learning (ML) and physics-informed algorithms for hyperspectral data analysis.Develop spectral unmixing, classification, and regression models tailored to diverse geospatial applications.Translate domain-specific science (agriculture, mineralogy, ecology, aquatics) into validated algorithmic methodologies.Utilize modern AI tools to enhance code generation and accelerate problem-solving.Pipeline ArchitectureConstruct and maintain scalable data processing pipelines on AWS for handling extensive geospatial datasets.Architect systems for radiometric correction, atmospheric compensation, and geometric orthorectification.Optimize processing pipelines for efficiency in throughput, latency, and cost management across petabyte-scale imagery.

About CartesiaAt Cartesia, we are on a mission to revolutionize artificial intelligence by creating interactive, ubiquitous intelligence that seamlessly adapts to your environment. Our groundbreaking approach tackles the challenge of processing and reasoning over extensive streams of audio, video, and text—1 billion text tokens, 10 billion audio tokens, and 1 trillion video tokens—all while maintaining on-device functionality.Founded by PhDs from the Stanford AI Lab who pioneered State Space Models (SSMs), we combine profound expertise in model innovation and systems engineering with a design-oriented product engineering team. Our aim is to build and deploy cutting-edge models and experiences that push the boundaries of AI.Supported by prominent investors including Index Ventures and Lightspeed Venture Partners, alongside a network of exceptional advisors and over 90 angel investors from diverse industries, we are at the forefront of AI advancement.The RoleAs a Senior Applied Researcher in Audio Understanding, you will confront some of the most complex challenges in audio perception. Your work will extend beyond traditional speech recognition to encompass a comprehensive range of audio understanding tasks, such as speaker identification, emotional interpretation, and navigation of intricate acoustic environments. You'll spearhead high-impact projects that are essential to our vision of developing truly aware AI.What You’ll DoDesign and implement innovative, large-scale models for complex audio understanding tasks, including multi-speaker automatic speech recognition (ASR), diarization, and non-speech audio classification, deploying them effectively at scale.Lead groundbreaking research in areas such as self-supervised learning for audio, few-shot learning, and resilient audio-visual perception.Establish new benchmarks and evaluation standards for our audio understanding systems.Create and manage extensive pre-training and fine-tuning datasets to enhance audio understanding capabilities.What We’re Looking ForIn-depth expertise in ASR, audio understanding, language modeling, or generative modeling.Experience with large-scale training, GPU/TPU acceleration, and model optimization.A strong practical mindset—capable of integrating scientific rigor with real-world applications.

TRANSFORMING MANUFACTURINGAt Bright Machines®, we are at the forefront of revolutionizing the manufacturing industry. Our team of dedicated innovators and experts collaborates to establish a new standard for manufacturing that leverages software and data to effectively address our clients’ unique challenges. With intelligent automation, we empower factories with enhanced flexibility, scalability, and resilience, ensuring they can meet today’s demands while preparing for the future.Joining our team means having the opportunity to drive meaningful change for both our organization and our clients. If you are eager to utilize your exceptional abilities to help create the factories of tomorrow, we would love to connect with you.ROLE OVERVIEWAs the Director of Strategy & Operations at Bright Machines, you will work closely with the CEO and the executive leadership team to spearhead high-impact initiatives throughout the organization. In this pivotal role, you will serve as a strategic and operational partner, driving cross-functional initiatives, advancing strategic priorities, and enhancing organizational effectiveness. Your contributions will be essential in shaping the company’s direction, facilitating decision-making processes, and ensuring efficient and cohesive execution across the business as it scales.

Join a pioneering team of former Google engineers who have developed ground-breaking defensive technologies, such as Safe Browsing and reCAPTCHA. We are on a mission to confront an urgent challenge: combating the rising tide of adversarial AI attacks that threaten organizations globally.Operating in stealth mode, we are targeting a lucrative $5B+ market that is primed for innovation. Conventional detection methodologies are proving inadequate against the speed and sophistication of AI-driven assaults. Current adversaries are leveraging AI to engineer tailored, high-evasion attacks, leaving traditional systems vulnerable.Your Role:You will design a network of AI agents that are rapid, cost-effective, and precise, collaborating to identify and neutralize emerging threats. Your work will dive deep into real-time threat data, continuously evolving your agents in a fast-paced environment. These agents will function under an orchestration layer that fosters quick adaptation and learning.The Excitement of the ChallengeRapidly Evolving Models: The landscape changes daily; solutions that worked yesterday may be outdated today.Intelligent Adversaries: We are engaged in a real-time arms race against cunning, AI-enhanced attackers crafting sophisticated payloads.No Existing Playbook: We are forging new detection paradigms as swiftly as threats evolve. This high-stakes work places you in the heart of the action from day one.If you thrive on solving challenging problems with rapid feedback, this is your opportunity.Why We Are Positioned to SucceedExpansive Market: The market is vast at $5B and expanding quickly, while established players struggle to adapt.Proven Track Record: Our team has previously developed the foundational technology for Safe Browsing (serving over 5B users) and reCAPTCHA (protecting more than 5M websites) during our time at Google.Experienced Team: This is our third endeavor in creating a category-defining security enterprise, and we know how to scale our technology and our organization effectively.Deeply Integrated AI and Security: We embed AI from the outset rather than layering it on top.Top Talent: We hire only the highest achievers; many on our team were in the top 1% of engineers at Google. If you excelled in your previous role, you will fit right in.Agility: We prioritize speed and efficiency in everything we do.

Why Join Achira?Become part of an exceptional team comprised of scientists, ML researchers, and engineers dedicated to transforming the landscape of drug discovery.Engage with cutting-edge machine learning infrastructure at an unprecedented scale, leveraging extensive computing resources, vast datasets, and ambitious goals.Take ownership of significant projects from conception through to architecture and deployment on large-scale infrastructures.Thrive in a culture that values thoroughness, speed, and a proactive, builder-oriented mindset.About the RoleAt Achira, we are developing state-of-the-art foundation models that address the most complex challenges in simulation for drug discovery and beyond. Our atomistic foundation simulation models (FSMs) serve as comprehensive representations of the physical microcosm, encompassing machine learning interaction potentials (MLIPs), neural network potentials (NNPs), and various generative model classes.We are looking for a Software Engineer who is enthusiastic about distributed computing and its applications in machine learning. You will play a pivotal role in designing and constructing the infrastructure for our ML data generation pipelines, model training, and fine-tuning workflows across large-scale distributed systems.Your expertise will be crucial in ensuring our compute clusters are efficient, observable, cost-effective, and dependable, enabling us to advance the frontiers of ML development. If you are passionate about distributed systems, performance optimization, and cloud cost efficiency, we encourage you to apply.You will be empowered to conceptualize and manage complex workloads across multiple vendors worldwide. Achira's mission revolves around computation, and providing seamless access to our uniquely tailored workloads at the lowest possible cost is critical to our success.

About the TeamThe Safety Systems team is dedicated to ensuring the responsible deployment of our advanced AI models for societal benefit. We lead OpenAI's mission to develop and implement safe AGI, prioritizing transparency and trust in our AI systems.The Model Safety Research team is focused on pioneering research to enhance the robustness and safety of AI models. Our goal is to tackle the evolving safety challenges that arise as AI becomes increasingly powerful and prevalent across various applications. Key areas of focus include the enforcement of nuanced safety policies, model robustness against adversarial threats, addressing privacy and security concerns, and ensuring trustworthiness in critical safety domains.We are committed to understanding real-world deployment and maximizing the benefits of AI while ensuring its safe and responsible use.About the RoleOpenAI is on the lookout for a passionate and experienced Senior Researcher specializing in AI safety. This role will guide research initiatives aimed at enabling safe AGI and will involve working on projects that enhance the safety, alignment, and robustness of our AI systems against adversarial threats. You will play a pivotal role in shaping the future of safe AI at OpenAI, significantly contributing to our mission of deploying safe AGI.In this role, you will:Engage in cutting-edge research on AI safety topics such as Reinforcement Learning from Human Feedback (RLHF), adversarial training, and system robustness.Implement innovative methods within OpenAI’s core model training processes and drive safety enhancements across our products.Define research directions and strategies to bolster the safety, alignment, and robustness of our AI systems.Collaborate with cross-functional teams, including Trust & Safety, legal, and policy experts, to ensure our products uphold the highest safety standards.Continuously assess and analyze the safety of our models and systems, pinpointing risks and proposing effective mitigation strategies.You might thrive in this role if you:Have a strong enthusiasm for AI safety and a solid background in safety research.Possess excellent analytical skills and the ability to think critically about complex safety challenges.Are adept at collaborating with diverse teams and communicating findings effectively.Have a proactive approach to problem-solving and a commitment to ethical AI deployment.

About Our TeamThe Training Runtime team is at the forefront of developing a sophisticated distributed machine-learning training runtime that supports everything from initial research prototypes to cutting-edge model deployments. Our mission is twofold: to enhance the capabilities of researchers and to facilitate large-scale model training. We are creating a cohesive and flexible runtime environment that evolves with researchers as they scale their projects.Our initiatives revolve around three key pillars: optimizing high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; constructing resilient, fault-tolerant training frameworks (including robust training loops, effective state management, resilient checkpointing, and comprehensive observability); and managing distributed processes for long-duration, job-specific uses. By embedding established large-scale functionalities into a user-friendly runtime, we empower teams to iterate rapidly and operate reliably at any scale, working closely with model-stack, research, and platform teams. Our success is measured in terms of both training throughput (the speed at which models are trained) and researcher efficiency (the speed at which concepts transform into experiments and products).About the PositionAs a Machine Learning Framework Engineer on our Training team, you will be pivotal in enhancing the training throughput of our internal framework while empowering researchers to explore innovative ideas. This role demands exceptional engineering skills, including the design, implementation, and optimization of state-of-the-art AI models, as well as writing clean, efficient machine learning code—a task that is often more challenging than it seems. A deep understanding of supercomputer performance metrics will also be critical. Ultimately, every project you undertake will aim to advance the field of machine learning.We seek individuals who are passionate about performance optimization, have a solid grasp of distributed systems, and have an aversion to bugs in their code. Given that our training framework is utilized for extensive runs involving numerous GPUs, any performance enhancements will significantly impact our operations.This position is based in San Francisco, CA, and adheres to a hybrid work model requiring three days in the office each week. We also provide relocation assistance for new hires.Key Responsibilities:Implement advanced techniques within our internal training framework to maximize hardware efficiency during training sessions.Conduct profiling and optimization of our training framework to enhance performance.Collaborate with researchers to facilitate the development of next-generation machine learning models.You Will Excel in This Role If You:Possess a strong passion for optimizing system performance.Have a profound understanding of distributed systems and their complexities.Demonstrate meticulous attention to detail, especially in code quality and debugging.

About Our TeamJoin the innovative Frontier Evaluations & Environments team at OpenAI, where we are dedicated to building transformative model environments that pave the way for safe artificial general intelligence (AGI) and artificial superintelligence (ASI). Our team constructs ambitious evaluation environments that not only measure but also enhance the capabilities of our models, creating self-improvement loops that inform our training, safety, and deployment strategies. Some of our notable open-source evaluations include GDPval, SWE-bench Verified, MLE-bench, PaperBench, and SWE-Lancer. We have also executed frontier evaluations for groundbreaking models like GPT4o, o1, o3, GPT 4.5, ChatGPT Agent, and GPT5. If you are passionate about experiencing firsthand the rapid advancements of our models and guiding them toward a positive impact, this is the opportunity for you.Your RoleWe are in search of exceptional research engineers who are eager to push the limits of our frontier models. Our ideal candidates will play a vital role in shaping our empirical understanding of AI capabilities across a broad spectrum and will take ownership of specific projects from conception to execution.Key Responsibilities:Design and implement ambitious reinforcement learning environments to maximize our models' potential.Conduct assessments of frontier model capabilities, skills, and behaviors.Create innovative methodologies for the automated exploration of model behaviors.Guide training processes for our most extensive model training initiatives, gaining insights into the future of AI.Collaborate with cross-functional teams to align model evaluations with organizational objectives.

Join Our Innovative TeamAt OpenAI, we are pioneering the field of artificial intelligence, empowering innovation and shaping the future through transformative research. Our mission is to democratize AI, ensuring its benefits are accessible to all. We are on the lookout for forward-thinking Research Engineers to join our Applied Group, where you will convert groundbreaking research into practical applications that can revolutionize industries, enhance human creativity, and tackle complex challenges.Your Impactful RoleAs a Research Engineer within OpenAI's Applied Group, you will collaborate with some of the brightest minds in AI. Your work will involve deploying cutting-edge models in production settings, transforming theoretical breakthroughs into impactful solutions. If you are passionate about making AI technology accessible and effective, this is your opportunity to leave a significant impact.In this role, you will:Innovate and Deploy: Create and implement advanced machine learning models addressing real-world issues. Translate OpenAI's research from theory to practice, developing AI-driven applications that make a meaningful difference.Collaborate with Experts: Engage closely with researchers, software engineers, and product managers to comprehend intricate business challenges and deliver AI-based solutions. Become part of a vibrant team where creativity and ideas flourish.Optimize and Scale: Develop scalable data pipelines, fine-tune models for peak performance and precision, and ensure readiness for production. Contribute to projects that leverage state-of-the-art technology and innovative methodologies.Learn and Lead: Stay at the forefront of advancements in machine learning and AI. Participate in code reviews, share insights, and exemplify best practices to maintain high standards in engineering.Make a Difference: Oversee and maintain deployed models, ensuring they consistently deliver value. Your contributions will directly shape how AI benefits individuals, businesses, and society as a whole.You may excel in this position if you possess:A Master's or PhD in Computer Science, Machine Learning, Data Science, or a related discipline.Proven experience in deep learning and transformer models.Expertise with frameworks such as PyTorch or TensorFlow.A robust understanding of data structures, algorithms, and software engineering principles.Experience with cloud platforms and deploying machine learning models in production.

About the TeamJoin the innovative Post-Training team at OpenAI, where we focus on refining and elevating pre-trained models for deployment in ChatGPT, our API, and future products. Collaborating closely with various research and product teams, we conduct crucial research that prepares our models for real-world deployment to millions of users, ensuring they are safe, efficient, and reliable.About the RoleAs a Research Engineer / Scientist, you will spearhead the research and development of enhancements to our models. Our work intersects reinforcement learning and product development, aiming to create cutting-edge solutions.We seek passionate individuals with robust machine learning engineering skills and research experience, particularly with innovative and powerful models. The ideal candidate will be driven by a commitment to product-oriented research.This position is located in San Francisco, CA, and follows a hybrid work model requiring three days in the office each week. Relocation assistance is available for new employees.In this role, you will:Lead and execute a research agenda aimed at enhancing model capabilities and performance.Work collaboratively with research and product teams to empower customers to optimize their models.Develop robust evaluation frameworks to monitor and assess modeling advancements.Design, implement, test, and debug code across our research stack.You may excel in this role if you:Possess a deep understanding of machine learning and its applications.Have experience with relevant models and methodologies for evaluating model improvements.Are adept at navigating large ML codebases for debugging purposes.Thrive in a fast-paced and technically intricate environment.About OpenAIOpenAI is a pioneering AI research and deployment organization dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We are committed to pushing the boundaries of AI capabilities while prioritizing safety and human-centric values in our products. Our mission is to embrace diverse perspectives, voices, and experiences that represent the full spectrum of humanity, as we strive for a future where AI is a powerful ally for everyone.

About Our TeamJoin the dynamic Support Automation team at OpenAI, where we utilize cutting-edge AI technologies to tackle real-world challenges and automate processes across our organization. Our mission is to enhance productivity from customer operations to engineering by building a suite of automation tools that empower our team members. We are dedicated to creating innovative products that prioritize quality and reliability through rapid prototyping and reusable solutions applicable across various sectors within OpenAI.In summary, our team harnesses OpenAI's technology to improve our internal processes, and you will have the unique opportunity to access both public and pre-released technologies to achieve this goal.About the RoleWe are seeking a talented Backend Software Engineer with substantial experience in machine learning and large language models to help us design and implement an evaluation infrastructure that measures the effectiveness of OpenAI's support automation efforts. This role is highly technical and collaborative, requiring you to build resilient systems and backend services that underpin knowledge creation, access, and application throughout OpenAI. You will work closely with Data Science and Research teams to scale evaluations effectively.Key Responsibilities:Design and implement evaluation pipelines that are dependable, reproducible, and scalable.Develop infrastructure for continuous evaluation monitoring, including regression and drift monitoring, and establish robust feedback loops to enhance support automation.Create, maintain, and support backend services and APIs that facilitate intelligent automation and knowledge systems.Integrate and organize data across internal platforms, optimizing it for downstream systems and AI workflows.Collaborate closely with data, research, and engineering teams to effectively integrate OpenAI models into impactful workflows.Oversee the full development lifecycle of new backend systems and internal platform features.Design with scalability and maintainability in mind while iterating rapidly on innovative ideas.Ideal Candidate Profile:4+ years of experience in backend engineering within product-focused companies (excluding internships).Proficient in designing and building reliable backend systems, with a strong understanding of machine learning principles.Experience collaborating across teams to drive project success and impact.

About Pax HistoriaPax Historia is pioneering a new genre of gameplay by leveraging cutting-edge generative AI technologies. Our innovative platform combines the strategic depth of grand strategy games with the limitless creativity of a sandbox environment, driven by a vibrant community that actively creates and modifies scenarios.Our user base generates hundreds of scenarios daily and engages in millions of game rounds each week, exhibiting rapid growth. We are proud to be supported by esteemed investors such as Y Combinator, Pace Capital, and Z Fellows. Your contributions will have an immediate impact on a product enjoyed by hundreds of thousands of players.Position OverviewWe are seeking a founding-level ML Systems Engineer to join our team in-person full-time in San Francisco (Dogpatch). You will have the opportunity to work closely with our cofounders to shape the future of our technology.Current Challenges:Closed-source models yield satisfactory game performance but come with high costs.Open-source models are more budget-friendly yet often underperform in our environment.Prompts and harnesses exhibit minimal variance across models.We have a functional internal evaluation system with significant opportunities for enhancement.Your Responsibilities:Establish and manage the necessary infrastructure for customizing harnesses and prompts tailored to individual AI models to optimize their performance.Develop domain-specific models aimed at narrowing or completely bridging the gap in performance between open and closed models.Optimize caching strategies to decrease expenses associated with closed-source models.Enhance the performance of closed-source models by training specialized endpoints.Assess and advance the effectiveness of embedding and reranking mechanisms in our applications.Facilitate the creation of new user experiences based on emerging world models.In Summary: Your work will directly enhance the affordability and enjoyment of the game.

Join Our Team as an AI Infrastructure EngineerAt Spellbrush, the premier generative AI studio behind niji・journey, we are in search of a talented AI Infrastructure Engineer to help us develop and enhance our end-to-end machine learning infrastructure, facilitating the operation of our models across a variety of platforms.Key Responsibilities:Design, implement, and maintain next-generation inference architecture to optimize the performance of our models across mobile, web, and other platforms.Collaborate with a dynamic team focused on creating cutting-edge image generation models that serve over 16 million users globally.Ideal Candidate Profile:Experience with Large Distributed Systems: You possess a strong background in working with modern technologies such as Kubernetes (K8S), Kafka, NATS, Redis, among others. Your hands-on experience spans both on-premises and multi-cloud environments, and you understand the intricacies and potential pitfalls of each system.Expertise in GPU Workloads: Your understanding of GPU processing for handling substantial workloads sets you apart. Having experience in deploying or optimizing GPU workloads end-to-end is a significant advantage.Passion for Anime Aesthetics: As avid anime enthusiasts, we value team members who share our passion for the anime aesthetic, contributing to a creative movement that engages millions.Team Player in Fast-Paced Environments: You thrive in small, agile teams and are eager to work alongside some of the world's top AI researchers, contributing to the best image models globally. We believe in the power of in-person collaboration, with opportunities at our offices in Tokyo (downtown Akihabara) or San Francisco. Visa sponsorships are available.