Performance Advisor

Role overview The Performance Modeling Lead at OpenAI works from San Francisco and takes on both technical and leadership responsibilities. This position centers on developing new modeling methods that enhance performance across a variety of applications. Alongside direct technical contributions, the role involves guiding a team and shaping project direction. What you will do Develop and improve modeling strategies to raise performance metrics for multiple projects. Use expertise in data analysis, machine learning, and optimization to address complex problems. Lead and mentor a team, supporting their technical development and ensuring strong project outcomes.

Role overview The Performance Modeling Engineer II position at OpenAI centers on building and applying performance models to enhance the efficiency of advanced AI systems. Based in San Francisco, this role contributes to the reliability and speed of OpenAI’s technologies. What you will do Develop and implement performance models for AI systems Collaborate with data scientists and engineers to refine performance metrics Support the efficiency and rigorous standards of OpenAI’s technologies

OpenAI is seeking a Performance Modeling Engineer based in San Francisco. This role centers on building and improving models that enhance the performance and efficiency of AI systems. The work directly supports the technical backbone of OpenAI’s products. Key responsibilities Develop and refine models aimed at optimizing the performance of AI systems. Collaborate with engineers and data scientists to tackle technical challenges as they arise. Contribute to projects that improve the efficiency of large-scale AI infrastructure. Role overview This position offers the chance to work on foundational technology that underpins OpenAI’s products. The focus is on practical improvements and close teamwork with technical colleagues to advance the capabilities and efficiency of AI at scale.

OpenAI is seeking a Software Engineer in San Francisco to focus on improving productivity by optimizing model performance. This position centers on developing solutions that make machine learning models more efficient and effective. Role overview This role involves working closely with teams across different functions to identify and address areas where model performance can be improved. The aim is to deliver changes that have a measurable impact on both systems and workflows. What you will do Collaborate with engineers and other specialists to enhance model efficiency Develop and implement solutions that improve the effectiveness of machine learning systems Contribute to projects that streamline processes and drive productivity gains Impact Your work will help shape improvements in how models operate and how teams at OpenAI achieve their goals. The changes you help deliver will support more effective use of resources and better outcomes for the organization.

ABOUT BASETENAt Baseten, we empower the most innovative AI companies—such as Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer—by providing a robust platform for mission-critical inference. Our unique combination of applied AI research, adaptable infrastructure, and cutting-edge developer tools allows companies at the forefront of AI to deploy state-of-the-art models seamlessly. Having recently secured a $300M Series E funding round from notable investors including BOND, IVP, Spark Capital, Greylock, and Conviction, we are poised for rapid growth. Join us in creating the essential platform for engineers to launch AI products.THE ROLEAre you driven to push the boundaries of artificial intelligence while leading a team of talented engineers? We are seeking a Technical Lead Manager with a focus on machine learning performance and inference. This position is perfect for an individual with a strong engineering foundation who is eager to guide and mentor a team while remaining actively engaged in hands-on technology work. If you excel in a dynamic startup atmosphere and are excited to tackle both leadership and technical challenges, we invite you to apply.EXAMPLE INITIATIVESAs a member of our Model Performance team, you will work on projects such as:Baseten Embeddings Inference: The fastest embeddings solution availableThe Baseten Inference StackDriving model performance optimizationRESPONSIBILITIESLead, mentor, and manage a team of engineers dedicated to developing and optimizing ML model inference and performance.Oversee technical strategy and architectural decisions, fostering improvements across our engineering organization.Collaborate with cross-functional teams to ensure the seamless integration and scalability of ML models in production settings.Drive innovation in model performance and advocate for best practices within the team.

Why Collaborate with Stand: Join us at Stand Insurance, where you will contribute to a revolutionary approach to global property protection. With the integration of cutting-edge physics and artificial intelligence, we meticulously assess catastrophic risks at the asset level, streamlining underwriting and loss mitigation processes. Our innovative risk engine is the true product we offer, redefining traditional insurance paradigms.At Stand, we step in when conventional insurers withdraw. We create precise models where others merely estimate. Our systems are designed to drive substantial outcomes rather than merely adjusting prices.Our Vision: The property insurance landscape has historically focused on pricing losses post-event, relying on outdated proxies and reactive strategies. At Stand, we break this mold by simulating real-world catastrophes' impacts on individual properties, translating these insights into actionable strategies, and automating our operations. This leads to a platform capable of underwriting risks that others cannot, all while minimizing friction.Your Role: As the Physics Team Lead within our Applied Science team, you will spearhead the development of foundational physics-based simulation capabilities, particularly in relation to wildfire and future risks. This role encompasses technical leadership and team management, evolving as our team expands.Your expertise in physics-based simulation will be pivotal in transforming traditionally high-cost engineering workflows into scalable, validated systems ready for production. These systems will significantly influence risk decisions and yield substantial business impacts.You will be responsible for the development and practical application of our core physics-based risk analytics programs. This includes ensuring that simulations are cohesive across different scales, informing probabilistic risk models, and integrating AI-driven techniques to achieve real-world results.This position is perfect for individuals who excel in dynamic environments, create order from uncertainty, take ownership of outcomes, collaborate across various disciplines, and are motivated by the challenge of building innovative solutions from the ground up.Your Responsibilities:Lead intricate, cross-disciplinary technical initiatives, coordinating efforts across data pipelines, backend orchestration, frontend visualization, and collaboration with subject matter experts, numerical simulation specialists, and machine learning engineers.Serve as the functional technical lead within the Applied Science team, harmonizing tasks across various scales and perils while establishing modeling standards and validation methodologies.Oversee major features within the physics simulation roadmap, including solver development, model calibration, and validation processes.

ABOUT BASETENBaseten is at the forefront of AI technology, empowering leading-edge companies like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer to seamlessly integrate advanced AI models into their operations. Our unique blend of applied AI research, adaptable infrastructure, and intuitive developer tools enables innovators to bring their most ambitious AI products to life. With our recent $300M Series E funding from top-tier investors such as BOND, IVP, Spark Capital, Greylock, and Conviction, we are poised for rapid growth. Join us in shaping the platform that engineers rely on to deploy transformative AI solutions.THE ROLEAre you driven by a passion for enhancing artificial intelligence applications? We are seeking a proactive Software Engineer specializing in ML performance to join our energetic team. This position is perfect for backend engineers who thrive in a fast-paced startup environment and are eager to make substantial contributions to the realm of Large Language Model (LLM) Inference. If you're enthusiastic about optimizing open-source ML models, we can't wait to hear from you!EXAMPLE INITIATIVESAs a member of our Model Performance team, you will have the opportunity to work on exciting projects, including:Baseten Embeddings Inference: The quickest embeddings solution availableThe Baseten Inference StackDriving model performance optimizationRESPONSIBILITIESDevelop, refine, and implement advanced techniques (quantization, speculative decoding, kv cache reuse, chunked prefill, and LoRA) for ML model inference and infrastructure.Conduct thorough investigations into the codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to troubleshoot and resolve ML performance issues.Scale and apply optimization techniques across a diverse array of ML models, with a focus on large language models.

Join fal as we revolutionize the generative-media infrastructure landscape. Our mission is to enhance model inference performance, enabling creative experiences on an unprecedented scale. We are seeking a Staff Technical Lead for Inference & ML Performance, an individual who possesses a unique blend of deep technical knowledge and strategic foresight. In this pivotal role, you will lead a talented team dedicated to building and optimizing cutting-edge inference systems. If you're ready to influence the future of inference performance in a fast-paced and rapidly growing environment, we want to hear from you.Why This Role MattersIn this role, you will play a crucial part in shaping the future of fal’s inference engine, ensuring that our generative models consistently deliver outstanding performance. Your contributions will directly affect our capacity to swiftly provide innovative creative solutions to a diverse clientele, from individual creators to global brands.Your ResponsibilitiesDefine and steer the technical direction, guiding your team across various domains including kernels, applied performance, ML compilers, and distributed inference to develop high-performance solutions.

About Plaud Inc.Plaud is at the forefront of developing the most reliable AI work companion designed for professionals, enhancing productivity through innovative note-taking solutions. Since our inception in 2023, we have garnered the trust of over 1,500,000 users globally. Our mission is to enhance human intelligence by creating state-of-the-art intelligence infrastructure and interfaces that effectively capture, extract, and utilize information from verbal, auditory, visual, and cognitive inputs.Headquartered in San Francisco, Plaud Inc. is a Delaware-incorporated company that is redefining human-AI collaboration through a unique synergy of hardware and software solutions. We prioritize the highest standards of data security and privacy, being compliant with SOC 2, HIPAA, GDPR, ISO27001, ISO27701, and EN18031.To discover more about our offerings, please visit https://www.Plaud.ai and connect with us on Instagram, X, Facebook, LinkedIn, and YouTube.

Join our dynamic team at dstaff as a Consumer Lead Quantitative Modeler. In this pivotal role, you will leverage advanced quantitative analysis to drive consumer behavior insights, improve strategic decision-making, and enhance our predictive modeling capabilities. You'll collaborate with cross-functional teams to deliver actionable solutions that impact business outcomes.

Join Samsara as a Senior Performance Marketing Manager specializing in Affiliate Advertising and Lead Buying. In this pivotal role, you will be responsible for developing and executing innovative marketing strategies that drive customer acquisition and enhance brand visibility. Collaborate with cross-functional teams to optimize campaigns, analyze performance metrics, and ensure alignment with business objectives.

Zyphra is an innovative artificial intelligence company located in the heart of San Francisco, California.The Opportunity:Join our dynamic team as a Research Engineer - Audio & Speech Models, where you will play a pivotal role in advancing Zyphra’s Audio Team. You will be instrumental in developing cutting-edge open-source text-to-speech and audio models. Your contributions will span the full spectrum of the model training process, from data collection and processing to the design of innovative architectures and training approaches.Your Responsibilities:Conduct large-scale audio training operationsOptimize the performance of our training infrastructureCollect, process, and evaluate audio datasetsImplement architectural and methodological improvements through rigorous testingWhat We Seek:A strong research mindset with the ability to navigate projects from ideation to implementation and documentation.Proficiency in rapid prototyping and implementation, allowing for swift experimentation.Effective collaboration skills in a fast-paced research environment.A quick learner who is eager to embrace and implement new concepts.Excellent communication abilities, enabling you to contribute to both research and engineering tasks at scale.Preferred Qualifications:Expertise in training audio models, such as text-to-speech, ASR, speech-to-speech, or emotion recognition.Experience with training audio autoencoders.Solid understanding of signal processing, particularly in audio.Familiarity with diffusion models, consistency models, or GANs.Experience with large-scale (multi-node) GPU training environments.Strong understanding of experimental methodologies for conducting rigorous tests and ablations.Interest in large-scale, parallel data processing pipelines.Competence in PyTorch and Python programming.Experience contributing to large, established codebases with rapid adaptation.

Earnest is dedicated to empowering ambitious individuals to make informed financial decisions and create the lives they aspire to lead.Our team, known as Earnies, is passionate about providing borrowers with smarter borrowing solutions that offer a clearer path toward financial empowerment. If you share our enthusiasm for this mission, we invite you to explore the details below and join us in building something exceptional.The Senior Model Risk Manager will report directly to the Head of Credit Risk.In this role, you will:Take ownership of and enhance Earnest’s Model Risk Management framework, ensuring that our credit, loss forecasting, fraud, marketing, and finance models are robust, transparent, and scalable.Conduct independent end-to-end model validations, from conceptual soundness and data quality to performance monitoring and implementation review, providing constructive feedback to modeling teams.Collaborate closely with Data Science and Risk leaders early in the model design process to refine assumptions, enhance methodologies, and uplift modeling standards throughout the organization.Supervise model performance monitoring and proactively identify emerging risks, performance drift, or control deficiencies, ensuring timely and effective remediation.Produce clear, decision-ready validation reports and effectively communicate technical findings to drive impactful business outcomes and sound risk management decisions.Act as a trusted advisor on model governance, enabling Earnest to operate swiftly while maintaining the necessary discipline and controls of a leading lending platform.

About Redwood MaterialsRedwood Materials is pioneering a sustainable battery supply chain that integrates recovery, reuse, and recycling—enabling the circulation of critical minerals and facilitating the energy transition. Established in 2017, we are proud to offer low-cost, large-scale energy storage solutions and produce battery materials within the U.S. for the first time, utilizing batteries that are already in circulation.Modeling and Architecture Engineer, Energy StorageAs the technical lead of the Energy Storage Modeling and Architecture team, you will play a critical role in the design, development, and integration of Redwood Energy’s innovative second-life battery product. You will serve as the subject matter expert in creating a multiphysics and technoeconomic modeling platform that informs the system design of this cutting-edge battery energy storage solution. These models must be robust enough to accurately size future projects while remaining agile enough to facilitate a wide range of design decisions.Additionally, you will be tasked with operationalizing these insights into an algorithm that optimally manages the use of each battery pack on our premises, maximizing the value extracted before recycling. This model will dictate operational parameters, including state of charge (SOC) windows and charge/discharge powers, along with decisions regarding when to replace a pack and what to use as a replacement.The ideal candidate will be self-motivated, adaptable to a startup culture, and enthusiastic about tackling novel technical challenges. You should possess experience in leading modeling teams within the battery energy storage or electric vehicle sectors while being a first-principles thinker capable of initiating new modeling projects independently.

Join Hilberts as our Lead AI Performance Marketing Strategist, where you'll spearhead innovative marketing campaigns that leverage artificial intelligence to optimize performance. Collaborate with cross-functional teams to develop and execute strategies that enhance brand visibility and drive customer engagement.

About World Labs: At World Labs, we create foundational world models capable of perceiving, generating, reasoning, and interacting with the 3D environment. Our mission is to unlock the full potential of AI through spatial intelligence, transforming perception into action, reasoning into insight, and imagination into creation. We believe that spatial intelligence will revolutionize storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical realms. Our world-class team is driven by curiosity and passion, boasting diverse backgrounds in technology, from AI research and systems engineering to product design. This synergy fosters a tight feedback loop between our cutting-edge research and user-empowering products. Role Overview We are seeking an innovative Research Scientist specializing in generative modeling, especially diffusion models, to join our modeling team. This position is ideal for individuals with extensive expertise in applying diffusion models to images, videos, or 3D assets and scenes. While not mandatory, experience in any of the following areas will be considered a significant advantage: Large-scale model trainingResearch in 3D computer vision In this role, you will work closely with researchers, engineers, and product teams to translate advanced 3D modeling and machine learning techniques into practical applications, ensuring our technology stays at the forefront of visual innovation. This position entails substantial hands-on research and engineering work, taking projects from conception to production deployment. Key Responsibilities Design, implement, and train large-scale diffusion models for generating 3D worlds. Develop and experiment with large-scale diffusion models to introduce novel control signals, align with target aesthetic preferences, or optimize for efficient inference. Collaborate closely with research and product teams to comprehend and translate product requirements into actionable technical roadmaps. Contribute actively to all phases of model development, including data curation, experimentation, evaluation, and deployment. Continuously investigate and integrate the latest research in diffusion and generative AI. Serve as a key technical resource within the team, mentoring peers and promoting best practices in generative modeling and machine learning engineering.

About MeterAt Meter, we believe that networking is at the heart of technological advancement. We have innovatively unified the entire networking stack and are now on a mission to make it autonomous.Our team is developing a cutting-edge neural network-driven system designed to analyze raw computer networks, enabling us to address all networking challenges. As outlined on Meter.ai, we are creating models within a closed-loop system that utilizes real-time telemetry, logs, and network events to autonomously troubleshoot issues, enhance performance, and resolve challenges.To achieve this, we require not only exceptional models but also robust infrastructure that ensures our models have clean, versioned, and low-latency access to the necessary data throughout training, evaluation, and deployment phases.Why this Role is EssentialEach Meter network deployed in the field serves as a valuable data source for our Models team. However, without meticulous infrastructure design, this data risks becoming fragmented, outdated, or inconsistent. In this role, you will ensure that such pitfalls are avoided. You will be responsible for the core data interface that drives our model development, experimentation, evaluation, and real-time inference.This position is fundamental and offers a significant impact. Your contributions will shape the speed at which we can train new models, the reliability of their evaluations, and their seamless operation across hundreds of real-world networks. You will collaborate closely with modelers to deliver systems that are elegant, scalable, and robust.Your ResponsibilitiesDesign and implement the Models API: a unified interface for accessing training, evaluation, and deployment data across raw, transformed, and feature-engineered layers.Ensure backward compatibility and feature versioning across continually evolving schemas.Develop scalable pipelines to ingest, transform, and serve petabytes of data across Kafka, Postgres, and Clickhouse.Create CI/CD workflows that evolve the API in tandem with changes to the underlying data schema.Facilitate fine-grained querying of historical and real-time data for any network, at any point in time.Help establish and promote the principle of 'smart data, dumb functions': maximizing operations in the data layer to minimize downstream code complexity.Collaborate with modelers to co-design training frameworks that optimize performance.

About the TeamThe Preparedness team plays a crucial role within the Safety Systems organization at OpenAI, adhering to our Preparedness Framework.While frontier AI models promise to bring significant benefits to humanity, they also introduce substantial risks. The Preparedness team is dedicated to ensuring that the development of advanced AI models fosters positive outcomes. Our mission includes identifying, monitoring, and preparing for catastrophic risks associated with these technologies.Key Mission Objectives:Monitor and predict the evolving capabilities of frontier AI systems to identify misuse risks that could significantly impact society.Establish concrete procedures, infrastructure, and partnerships to mitigate these risks and ensure the safe development of powerful AI systems.This fast-paced and impactful role connects capability assessment, evaluations, internal red teaming, and mitigations for frontier models, facilitating coordination on AGI preparedness.About the RoleAs a Threat Modeler, you will spearhead OpenAI's comprehensive approach to identifying, modeling, and forecasting risks from frontier AI systems. Your work will ensure that our evaluation frameworks, safeguards, and classifications are robust, comprehensive, and future-focused. You will help articulate the rationale behind our most stringent risk-prevention strategies, influencing prioritization and mitigation across various domains. This position acts as a central hub, integrating technical, governance, and policy considerations regarding our approach to frontier AI risks.Key ResponsibilitiesDevelop and maintain comprehensive threat models across various misuse areas (biological, cyber, attack planning, etc.).Create plausible threat models addressing loss of control, self-improvement, and other potential risks associated with alignment from frontier AI systems.Forecast risks by merging technical foresight, adversarial simulation, and current trends.Collaborate closely with technical partners on capability evaluations and risk assessments.

About the RolePerplexity is seeking a talented Model Behavior Architect to join our innovative AI team in San Francisco. In this role, you will be instrumental in developing and evaluating AI products that enhance user experiences across various domains. Collaborating closely with both research and product teams, you will design strategies for prompt and context engineering that ensure high-quality interactions.This position uniquely blends creativity and analytical skills. You will gain a profound understanding of our answer engine by rigorously testing model capabilities and working with our AI infrastructure, including system prompts, tool prompts, skills, and evaluations, to create an exceptional product experience for our users.As the go-to expert on prompting, model quality, and behavioral consistency, you will be pivotal in the deployment of new product features and model releases.Key ResponsibilitiesContext Engineering: Create, test, and refine context strategies and system prompts that influence answer engine behavior across various products, features, and use cases.Evaluation Systems: Develop automated and semi-automated evaluation pipelines to assess model quality, detect regressions, and scale across product surfaces.Model Launch Support: Collaborate with research and engineering teams to validate model behavior prior to and during rollouts, ensuring seamless transitions without any degradation.Research & Analysis: Identify inconsistencies and potential failure modes in model outputs through meticulously designed research initiatives for both internal and production-facing systems.Cross-functional Collaboration: Work closely with design, product, and research teams to translate product objectives into specific model behavior requirements.Knowledge Sharing: Assist engineers across teams in developing a strong understanding of prompt design, context engineering, and evaluation best practices.Staying Current: Keep abreast of the latest alignment, evaluation, and prompting techniques from both industry and academia, and integrate the best ideas into the team.