Machine Learning Engineer at Reducto | San Francisco

About PoesisPoesis is a pioneering AI-native investment manager that is transforming the landscape of U.S. equities through innovative foundation models. We are developing cutting-edge AI systems designed to predict market trends and exceed the performance of traditional investment managers. This exciting work represents frontier research that is validated i…

About PoesisPoesis is an innovative AI-native investment management firm, leading the charge in developing a pioneering foundation model for investing in U.S. equities. We are crafting modular AI systems designed to predict market fluctuations and surpass traditional managers. This role involves engaging in cutting-edge research that yields immediate, real-world validation. Your contributions will play a crucial role in shaping investment strategies and enhancing portfolio outcomes.Location & WorkstyleBased in the San Francisco Bay Area (close to Stanford), this position is Hybrid: requiring several days on-site each week.Relocation assistance is available.About the RoleAt Poesis, we are establishing a machine learning-driven hedge fund focused on innovative trading strategies. We are seeking a Founding Quant Developer to transform research concepts into production-grade software. Collaborating closely with the Head of Engineering and Chief Scientist, you will develop data pipelines, implement models, and guarantee that results are clean, reproducible, and transparent.This role is highly hands-on and offers a steep learning curve, making it perfect for individuals with robust technical skills who are eager to gain experience in both engineering and quantitative finance within a startup environment. Expect strong guidance from Poesis’ Chief Scientist and CEO, as you will be accountable for converting their research ideas and specifications into thoroughly tested, production-ready code.

About AbacusAt Abacus, we are revolutionizing the operations of accounting firms through innovative AI agents that automate the monotonous and repetitive tasks currently faced by teams. Our cutting-edge core engine integrates advanced Optical Character Recognition (OCR) and Large Language Models (LLMs) to provide genuinely intelligent back-office automation solutions. We have already established partnerships with significant enterprise clients, generating substantial revenue, and are proudly supported by leading investors. Having achieved this milestone as a compact team of two, we are eager to expand our workforce. If you are passionate about shaping the future of AI-driven operations and are ready to take on impactful technical challenges from the outset, this is your opportunity.The RoleWe are seeking our inaugural Founding Engineer to take charge of and enhance the core machine learning engine that powers Abacus. Reporting directly to the co-founders, you will work on-site from our San Francisco office. This is a unique chance to join a rapidly growing company as an early engineer, endowed with significant autonomy and influence over both product and technical direction.In your first 3–6 months, you will:Enhance and scale our ML extraction engine utilizing LLMs and OCR technologies.Take ownership of backend architecture and infrastructure decisions.Develop and launch innovative features that broaden the scope of automated workflows.In the following year, you will play a pivotal role in establishing the foundation of our engineering organization as we scale, while remaining hands-on and focused on delivering impactful results.What You’ll DoLead the development of our machine learning-driven document extraction engine.Architect backend systems with an emphasis on performance and scalability.Create and deploy new automation features tailored for tax firms.Work closely with the founders to align on product and user requirements.Contribute to defining our engineering culture and establishing the technical roadmap.What We're Looking ForEssential Qualifications:1–5 years of experience, preferably in environments with high ownership or early-stage ventures.Proficient backend development skills, especially in Python.Demonstrated ability as a 0→1 builder, whether through side projects, startup experience, or both.Commitment to work from our SF office, five days a week.Willingness to complete a technical assessment as part of the application process.

Founding Machine Learning EngineerLocation: San Francisco, CA Work Model: In-office 5 days a weekAbout UsAt Effective AI, we are pioneering the future of work. Our vision is to push the boundaries of AI beyond mere repetitive tasks, focusing instead on intricate knowledge work that requires expertise and multi-faceted reasoning. We are developing advanced AI Teammates that are designed to navigate complex workflows and collaborate seamlessly with human professionals. Our initial focus is on the trillion-dollar U.S. Property & Casualty insurance sector, a domain rich with complexity and data, making it an ideal arena for our innovations.We proudly secured $10 million in seed funding from prominent investors including Lightspeed Ventures and Valor Equity Partners.Our committed team is based in San Francisco and thrives on in-person collaboration to tackle these significant challenges.Your RoleAs a Founding Machine Learning Engineer, you will be an integral member of our founding team, responsible for architecting, training, and deploying the agent loops that power our AI Teammates from inception. You will address some of the most pressing challenges in agentic AI and natural language processing, developing AI solutions adept at performing essential insurance functions such as underwriting and claims processing.Your responsibilities will include:Architecting and Developing Core ML Pipelines: Design, train, and fine-tune cutting-edge language models (including reinforcement learning agents) to facilitate long-term task accomplishment and complex decision-making.Implementing Nuanced Reasoning: Integrate machine learning techniques that empower agents to make informed decisions based on ambiguous or incomplete data, akin to human expert reasoning and generalization.Building Intelligent, Tool-Using Agents: Engineer the ML systems that enable our agents to dynamically select and utilize a broad array of external tools—including APIs, databases, web searches, and Excel-based pricing algorithms—to gather necessary information and execute actions.Designing and Implementing Robust Evaluation Frameworks: Create and employ comprehensive evaluation metrics and systems to rigorously assess and benchmark agent performance, identify areas for enhancement, and guarantee reliability and safety in real-world insurance processes.Enabling Continuous Adaptation and Learning: Develop resilient ML pipelines and feedback loops that facilitate ongoing learning and adaptation.

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.

About Taskrabbit:Taskrabbit is an innovative marketplace platform that seamlessly connects individuals with Taskers to manage everyday home tasks, including furniture assembly, handyman services, moving assistance, and much more.At Taskrabbit, we aim to transform lives one task at a time. We celebrate innovation, inclusion, and hard work, fostering a collaborative, pragmatic, and fast-paced culture. We seek talented, entrepreneurially minded, data-driven individuals who possess a passion for empowering others to pursue their passions. In partnership with IKEA, we are creating more opportunities for individuals to earn a consistent, meaningful income on their terms by establishing enduring relationships with clients in communities globally.Taskrabbit operates as a hybrid company, with team members located across the US and EU, and has been recognized as a Built In — Best Places to Work for 2022, 2023, and 2024, receiving accolades across various national and regional categories. Join us at Taskrabbit, where your contributions will be significant, your ideas appreciated, and your potential maximized!This position operates on a hybrid schedule, requiring two days of in-office collaboration per week. It can be based in our San Francisco office or our new New York City office (opening March 2026).About the RoleMachine Learning is a foundational element at Taskrabbit, and we are in search of an experienced Senior Machine Learning Engineer to join our team and help mold the future of ML/AI at Taskrabbit. This distinct, full-stack role is designed for someone who is enthusiastic about the entire machine learning lifecycle—from initial research and model development to constructing the robust infrastructure necessary for deploying and scaling your innovations.As a Senior Machine Learning Engineer, you will engage with exciting challenges that directly influence how users discover and interact with home services on the Taskrabbit platform. You will play a vital role in enhancing our capabilities in areas such as search ranking, content discovery, and recommendation systems. Collaborating closely with data scientists and fellow engineers, you will design and implement cutting-edge algorithms, ensuring the scalability, reliability, and optimization of our models in production alongside software engineers.

About VSCO At VSCO, we empower photographers with an innovative platform that provides essential tools, a vibrant community, and the visibility needed for creative and professional growth. We cultivate an authentic creative environment that welcomes photographers of all skill levels, offering a space that inspires opportunity, collaboration, and connection. Our mission is to support photographers in their journeys, enabling them to thrive and connect with fellow creatives and businesses through our comprehensive suite of tools, available on both mobile and desktop. We seek individuals who are passionate and proactive in advancing our mission. Our team members have the opportunity to make a significant impact, and we believe that collaborative efforts yield stronger results. Our core values are essential to our team culture and guide our hiring process. Learn more about what you can expect when joining VSCO on our Careers Page. About The Role As a Senior Machine Learning Engineer, you will harness the power of AI and machine learning to create innovative, reliable user-facing product features. You will leverage your extensive technical background and hands-on experience in deploying machine learning models to deliver impactful solutions based on real-world feedback. Your focus on measurable outcomes and customer satisfaction drives your work, blending innovation with practical implementation. You will be highly skilled in Python and adept across the data and machine learning stack, enabling you to develop and launch models efficiently while ensuring scalability and maintainability. Whether working with traditional algorithms or cutting-edge deep learning and generative AI, you will expertly navigate the complexity of each problem, managing every phase from defining the challenge to deployment and iterative improvement. Your dedication to software engineering excellence will inform your thoughtful approach to system design for machine learning, encompassing data quality, pipeline design, feature workflows, model serving, and ongoing monitoring and enhancement. By integrating machine learning deeply within our cohesive product experiences, you will collaborate effectively with cross-functional teams, aligning on objectives, defining success metrics, and driving meaningful outcomes. You will stay informed about the rapidly evolving AI landscape, maintaining a discerning perspective that allows your team to focus on significant advancements while avoiding distractions. The Day to Day Design and implement ML-powered features for search, discovery, personalization, and more.

Join Known as a Founding Machine Learning EngineerLocation: San Francisco, CA (In-Person)Salary: $200,000 - $375,000 Cash + EquityAt Known, we are revolutionizing the way people connect by utilizing advanced AI technology. Our mission is to enhance human relationships through intelligent matchmaking.Users engage with our AI voice assistant, sharing their personal stories for an average of 27 minutes, which provides us with a rich, multi-modal data set.Our team comprises seasoned engineers behind some of the most successful AI-driven consumer applications, including Uber Eats, Uber, Faire, and Afterpay.We value hard work, autonomy, and ownership, and collaborate in our Cow Hollow office in San Francisco.Explore More About Us:Download KnownOur Launch AnnouncementTechCrunch Feature on Our Seed FundingNew York Times Article on KnownFastCompany Review of KnownVisit Our Website

Job OverviewJoin Eragon as a Machine Learning Engineer and lead the charge in transforming innovative AI models into scalable, production-grade systems. This position is pivotal in bridging research and real-world applications by designing and optimizing systems that enhance vital workflows throughout the enterprise.In collaboration with our research, product, and engineering teams, you will convert cutting-edge capabilities into dependable, high-performance systems ready for production.Key ResponsibilitiesModel Development & Deployment: Craft, refine, and deploy machine learning models within production settings.Systems Engineering: Architect scalable pipelines for training, inference, evaluation, and comprehensive monitoring.Performance Optimization: Enhance the latency, throughput, cost-efficiency, and reliability of ML systems.Data & Infrastructure: Manipulate large datasets and ensure seamless integration of models with internal systems and APIs.Cross-Functional Collaboration: Collaborate with product and engineering teams to provide end-to-end AI functionalities.Evaluation & Monitoring: Develop robust evaluation frameworks and feedback loops to ensure system effectiveness.

At Sciforium, we are pioneering the future of AI infrastructure by creating cutting-edge multimodal AI models and a proprietary, high-efficiency serving platform. With substantial financial backing and direct support from AMD engineers, our team is rapidly expanding as we develop the comprehensive stack that drives advanced AI models and real-time applications.About the RoleIn the capacity of a Machine Learning Engineer, you will engage with the entire foundation-model stack, encompassing pretraining and scaling, post-training and Reinforcement Learning, sandbox environments for evaluation and agentic learning, and deployment + inference optimization. You’ll have the opportunity to rapidly iterate on research ideas, contribute to production-grade infrastructure, and help deliver models capable of addressing real-world challenges at scale.Your ResponsibilitiesThis position offers diverse tracks - candidates can specialize or contribute across multiple areas. Key responsibilities include:Pretraining & ScalingTrain expansive byte-native foundation models utilizing vast, heterogeneous data sources.Formulate stable training methodologies and scaling laws tailored for innovative architectures.Enhance throughput, memory efficiency, and resource utilization across extensive GPU clusters.Establish and maintain distributed training infrastructures alongside fault-tolerant pipelines.Post-training & Reinforcement LearningBuild out post-training frameworks (SFT, preference optimization, RLHF/RLAIF, RL).Curate and produce specialized datasets aimed at enhancing specific model capabilities.Develop reward models and evaluation systems to facilitate ongoing improvements.Investigate inference-time learning and computational strategies to boost performance.Sandbox Environments & EvaluationCreate scalable sandbox environments for agent assessment and learning.Generate realistic, high-signal automated evaluations for reasoning, tool usage, and safety.Design both offline and online environments that support RL-style training at scale.Implement instrumentation for observability, reproducibility, and rapid iteration.Deployment & Inference OptimizationOptimize deployment strategies to ensure models are efficient and effective in real-world applications.

About PoesisPoesis is an innovative AI-driven investment management firm that is redefining the foundational model for investing in U.S. equities. Our mission is to construct modular AI systems that predict market fluctuations and outpace traditional managers. This role involves engaging in cutting-edge research with immediate applicability in the financial markets. Your contributions will significantly influence investment strategies and enhance portfolio outcomes.Location & WorkstyleLocated in the San Francisco Bay Area, close to Stanford University, we offer a Hybrid work environment requiring several days of on-site presence each week.Relocation assistance is available.About the RoleAs we develop a machine learning-driven hedge fund focused on transforming trading decision-making, we are seeking our Founding Head of Engineering. This pivotal role marks the first engineering hire, responsible for shaping our technical architecture, establishing the initial system, and operating as both an individual contributor and product owner. You will collaborate closely with our CEO and Chief Scientist to develop the technical foundation of our fund.Your responsibilities will include designing and delivering the initial demonstrable workflows, integrating with financial data providers, constructing reproducible pipelines, and creating a user-friendly interface suitable for decision-makers and investors. As the company evolves, you will also play a key role in recruiting engineers and data scientists.

Join Strava, a leader in the sports technology sector, as a Machine Learning Engineer. In this exciting role, you will apply your expertise in machine learning and data science to develop innovative solutions that enhance the experience of millions of athletes worldwide. Collaborate with cross-functional teams to create algorithms that analyze vast datasets and provide actionable insights to our users.

About LightfieldLightfield is an innovative, AI-powered CRM that seamlessly integrates with your email, calendar, and meetings. It captures every interaction and transforms it into organized context, including accounts, tasks, follow-ups, and valuable insights, ensuring that nothing is overlooked.We are fundamentally reimagining CRM by focusing on the actual workflows of teams rather than imposing rigid systems. Lightfield learns from real-world usage, automating processes and surfacing insights that drive business growth. We’re creating the CRM platform we’ve always envisioned: fast, intelligent, and genuinely supportive.Supported by notable investors such as Greylock, Lightspeed, and Coatue, our team has a rich background, having previously developed Tome, a generative AI presentation tool utilized by over 25 million users. Many of us have experience with leading companies such as Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleAs a key member of Lightfield's AI/ML team, you will play a vital role in crafting the core experiences of our product, developing cutting-edge applications that delight our customers.Currently, our focus is on building a powerful, domain-specific AI that surpasses generic LLMs.We thrive on the challenge of creating groundbreaking AI products for professionals engaged in serious work, and we are eager to expand our AI/ML team to meet these ambitious goals.What You'll DoDevelop and deliver exceptional, unique AI experiences that sales teams will be excited to use.Collaborate with founders and executives to shape Lightfield's AI/ML strategy.Identify user needs suitable for AI/ML solutions, articulate challenges, and work closely with product leaders to devise solutions.Prototype innovative, LLM-powered experiences and guide their development into reliable product features.Contribute to building a world-class AI/ML engineering team through recruitment and mentorship.Who You ArePossess a BS or MS degree in Computer Science, Artificial Intelligence, or Applied Mathematics.Have over 5 years of experience in developing AI/ML products, particularly in Natural Language Processing (NLP).Demonstrate a solid understanding of deep learning AI/ML frameworks and cloud services.Bring hands-on experience in ML Operations (ML Ops).Bonus PointsExperience leading AI/ML product initiatives...

Machine Learning EngineerJoin our client, a pioneering company dedicated to developing state-of-the-art non-invasive technology for brain interfacing. They are at the forefront of creating an innovative ultrasound-based platform that not only stimulates but also images brain activity with unmatched precision and depth, paving the way for groundbreaking advancements in neurological treatments and health research.This integrated approach combines cutting-edge hardware, sophisticated real-time software systems, and applied neuroscience to produce scalable solutions that can enhance lives on a global scale.We are looking for a skilled Machine Learning Engineer to play a crucial role in designing and implementing the essential algorithms that will facilitate precise imaging and targeting of brain activity through ultrasound systems.

About the RoleJoin Onyx, an esteemed open-source project that has captivated hundreds of thousands of users. With over 10,000 stars and a vibrant community of over 3,000 members on platforms like Slack and Discord, your contributions could impact millions in the future. Your ImpactAs a Machine Learning Engineer at Onyx, you will play a pivotal role in enhancing our knowledge layer on top of Large Language Models (LLMs). You will tackle complex challenges such as multi-hop question answering, needle-in-haystack retrieval, and advanced Retrieval-Augmented Generation (RAG) techniques. Key ResponsibilitiesDesign and implement knowledge graphs based on LLMs, exploring advanced RAG methods and cutting-edge information retrieval algorithms.Enhance user experience through innovative features like feedback learning, personalized search, and Subject Matter Expert (SME) suggestions.Develop a semantic understanding of organizational priorities to improve Onyx's answering capabilities.Manage projects from initial conception through validation to production deployment.Collaborate closely with our Founders and Head of AI to shape product direction and contribute to our AI/ML strategy. Success Criteria3+ years of experience in AI/ML engineering, focusing on real-world applications.In-depth expertise with PyTorch/TensorFlow, natural language processing (NLP) models, and standard machine learning algorithms.Stay current with advancements in open-source and proprietary LLMs, RAG, and agent frameworks.Strong software engineering skills, capable of building backend features using web frameworks, ORMs, and relational databases.Excellent communication skills, with the ability to collaborate effectively across teams.⭐ Bonus SkillsFamiliarity with full-stack technologies, including TypeScript, React, Next.js, Python, and PostgreSQL.Passion for writing technical blogs to position Onyx as a leader in the field.

About ApiphanyApiphany is an innovative AI company dedicated to advancing physical product development. We empower global leaders in industries such as automotive, aerospace, medtech, and energy to convert vast amounts of unstructured technical data into immediate, actionable insights. Supported by elite investors including Markforged, Databricks, GM, and Character, our mission is to transform engineering decision-making, simplifying complexity for the world's premier manufacturers.Our models are meticulously crafted to address the unique challenges of engineering and manufacturing. They are designed to comprehend principles of physics, design specifications, and program constraints. Our team is a select group of experts from prestigious institutions like Stanford, Berkeley, MIT, UW, and CMU, alongside veterans from GM, Ford, and Genesis Therapeutics. We are committed to redefining hard-tech and constructing a category-defining enterprise together.About the RoleAs a Machine Learning Engineer at Apiphany, you will architect and deploy cutting-edge machine learning models to address some of the most intricate challenges within the physical domain. You will create systems capable of reasoning with complex engineering data, developing AI that grasps physics, design limitations, and real-world performance trade-offs.This role is tailored for innovators eager to expand the horizons of AI applications in the tangible world.

Join Our Team as a Machine Learning Engineer for AssessmentsAt Speak, we're on a mission to transform the language learning experience.Learning a new language has the power to enrich lives, facilitating connections with diverse cultures, career opportunities, and communities. With two billion people worldwide engaged in language studies, the traditional one-on-one tutoring approach remains challenging to scale and has seen little innovation over the years. Speak is revolutionizing this space by offering an AI-powered, human-like tutoring experience that prioritizes conversation. Our platform allows learners to practice speaking, receive instant feedback, and progress through expertly crafted lessons, ensuring a seamless journey from beginner to confident speaker in multiple languages.Since our inception in South Korea in 2019, Speak has rapidly ascended to become the leading language learning app, serving learners across various markets with 15+ languages. Backed by over $150 million in venture funding from prominent investors such as OpenAI, Accel, and Khosla Ventures, our distributed team spans San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.About the RoleWe are seeking a talented Machine Learning Engineer for Assessments to spearhead the development of top-tier assessment systems across our diverse product lines, including Speak for Business and B2C offerings. You will collaborate closely with our Assessment Design Lead, along with teams in Machine Learning, Product, and Engineering, to translate assessment frameworks and rubrics into robust, scalable scoring and feedback systems.This role will encompass the implementation, deployment, and continual enhancement of our assessment algorithms and ML systems. While immediate focus will be on refining and expanding current assessments, the work will also contribute to a foundational capability that can be leveraged across our platform.Your ResponsibilitiesLead the development of assessment ML systems end-to-endDesign, deploy, and maintain scoring models and pipelines (feature extraction, model training, inference, feedback generation).Oversee monitoring, regression tests, and iterative improvements to ensure accuracy standards are met.Establish and implement evaluation frameworksCreate validation and evaluation structures for assessments, incorporating metrics, test sets, and both offline and online analyses.Convert assessment needs into quantifiable acceptance criteria and safeguards.

About MercorMercor operates at the dynamic intersection of labor markets and artificial intelligence research. By collaborating with top-tier AI laboratories and enterprises, we provide the vital human intelligence needed for AI development.Our extensive network of over 30,000 experts trains cutting-edge AI models in a manner akin to educators nurturing students: through the exchange of knowledge, experience, and contextual insights that cannot be encoded. Collectively, our experts generate over $2 million in earnings each day.At Mercor, we're pioneering a new category of work where expertise fuels AI progression. This ambitious endeavor requires a fast-paced, dedicated team. You’ll collaborate with leading researchers, operators, and AI companies at the forefront of systems that are transforming society.As a profitable Series C company valued at $10 billion, we operate in-person five days a week at our state-of-the-art headquarters in San Francisco.

Join our innovative team at Osaro as a Machine Learning Engineer, where you will contribute to advancing the intelligence and capabilities of our robotic systems. Our cutting-edge products integrate advanced perception algorithms with adaptive decision-making and meticulous control strategies, empowering industrial robots to operate autonomously and efficiently across diverse applications.In this role, you will collaborate closely with our robotics, deployment, and sales teams to identify client requirements and design tailored machine learning solutions. You'll be responsible for monitoring, training, and validating the performance of our deep learning models, ensuring they meet our quality standards.We seek individuals who are not only passionate about their work but also take ownership of their projects and enjoy tackling new challenges. The ideal candidate is one who values teamwork and embodies integrity and directness in their communication.