Technical Staff Member - Pre-Training Infrastructure

Our MissionAt Reflection AI, our goal is to develop open superintelligence and make it universally accessible.We are pioneering open weight models tailored for individuals, agents, enterprises, and even entire nations. Our diverse team comprises talented AI researchers and industry veterans from prestigious organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic, and many more.Role OverviewConstruct and enhance distributed training systems that drive the pre-training of cutting-edge models.Collaborate with research teams to design and execute extensive training runs for foundational models.Create infrastructure that facilitates efficient training across thousands of GPUs leveraging contemporary distributed training frameworks.Enhance training throughput, stability, and efficiency for extensive model training tasks.Work closely with pre-training researchers to convert experimental concepts into scalable, production-ready training systems.Boost performance of distributed training tasks through optimization of communication, memory management, and GPU utilization.Develop and maintain training pipelines that accommodate large-scale datasets, checkpointing, and iterative experiments.Identify and resolve performance bottlenecks within distributed training systems, including model parallelism, GPU communication, and training runtime environments.Contribute to the creation of systems that promote swift experimentation and iteration on novel training methods.

Our MissionAt Reflection AI, we are dedicated to creating open superintelligence and making it universally accessible.We are pioneering open weight models designed for individuals, agents, enterprises, and even nations. Our talented team consists of AI researchers and innovators from leading organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, and Anthropic.Role OverviewData is becoming increasingly vital in the realm of AI advancements. Recent significant breakthroughs have frequently stemmed from enhanced data rather than new architectures.As a vital member of the Data Team, your primary role will be to guarantee that the data utilized for training our models adheres to the highest standards of quality, reliability, and impact. You will have a direct influence on our models' performance in essential capabilities.Collaborating with exceptional researchers on our pre-training teams, you will help transform abstract concepts of "good data" into specific, quantifiable standards applicable across extensive data campaigns. We are seeking engineers who possess robust engineering skills combined with a profound curiosity about data quality and its relevance to model performance.In close partnership with our pre-training teams, you will:Take ownership of upstream data quality for LLM pre-training, functioning as either a specialist or generalist across various languages and modalities.Collaborate with research and pre-training teams to convert requirements into measurable quality signals, providing actionable feedback to external data vendors.Incorporate human-in-the-loop processes while designing, validating, and scaling automated QA methods to consistently measure data quality across large-scale campaigns.Create reusable QA pipelines that ensure the delivery of high-quality data to pre-training teams for model training.Continuously monitor and report on data quality, driving ongoing improvements in quality standards, processes, and acceptance criteria.Candidate ProfileStrong engineering background with experience in building data pipelines, QA systems, or evaluation workflows for pre-training data.Detail-oriented with an analytical mindset, capable of identifying failure modes, inconsistencies, and nuanced issues affecting data quality.Solid understanding of the influence of data quality on pre-training, with the capacity to translate quality concerns into tangible signals, decisions, and feedback.

Our VisionAt Reflection AI, we are dedicated to developing open superintelligence and ensuring it is accessible to everyone.We are pioneering open weight models for individuals, agents, organizations, and even nations. Our diverse team of AI researchers and industry pioneers hail from esteemed organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic, and many others.Position OverviewIn the rapidly evolving field of AI, data has become indispensable for innovation. Notable progress in recent years has stemmed more from enhanced data quality than from novel architectures.As a valued member of our Data Team, you will be responsible for ensuring that the datasets used to train and assess our models are of exceptional quality, reliability, and effectiveness. Your contributions will directly influence our models' capabilities in areas such as agentic tool usage, long-term reasoning, and ensuring robust safety alignment.Collaborating with elite researchers within our post-training teams, you will help transform abstract concepts of “good data” into tangible, scalable standards for extensive data initiatives. We seek engineers who possess a strong foundation in engineering principles paired with a genuine curiosity about data quality and its effects on model performance.Working closely with our post-training teams, your responsibilities will include:Managing upstream data quality for LLM post-training and evaluations by analyzing expert-generated datasets and implementing quality benchmarks for reasoning, alignment, and agentic applications.Collaborating with research and post-training teams to translate requirements into quantifiable quality indicators and offering actionable insights to external data providers.Developing, validating, and expanding automated quality assurance methods, including LLM-as-a-Judge frameworks, to consistently assess data quality across large-scale projects.Creating reusable quality assurance pipelines that consistently supply high-quality data to post-training teams for model training and evaluation.Tracking and reporting on data quality trends over time, fostering continuous improvements in quality standards, processes, and acceptance criteria.QualificationsSolid engineering principles with experience in building data pipelines, quality assurance systems, or evaluation workflows tailored for post-training data and agentic environments.Meticulous and analytical, capable of pinpointing failure modes, inconsistencies, and nuanced issues that influence data quality.A robust understanding of the impact of data quality on model behavior and performance.

At Magic, we are on a mission to create safe AGI that propels humanity forward in tackling the world's most pressing challenges. We believe that the key to achieving safe AGI lies in automating research and code generation, allowing us to enhance models and ensure alignment more reliably than human capabilities alone. Our innovative approach integrates frontier-scale pre-training, domain-specific reinforcement learning, ultra-long context, and advanced inference-time computing to realize this vision.About the Role:We are seeking a passionate individual to spearhead developer experience and data tooling within our pre-training data team. This role involves creating internal tools and infrastructure that enhance team productivity, including dashboards, command-line interfaces (CLIs), data exploration UIs, and the systems that interconnect them.Focusing on developer experience and tooling, we need someone who enjoys solving problems, deploying solutions quickly, and experimenting with new ideas.Potential Projects:Lead tooling initiatives across the architecture: develop systems, implement continuous integration, create CLI utilities, and design internal web interfaces.Design internal tools for dataset exploration, data labeling, quality assessment, and data inventory management.Enhance data infrastructure ergonomics—optimizing IO patterns in Ray/dataflow jobs, improving dataset tracking, and enhancing pipeline observability.Spot opportunities by engaging with the team, understanding their challenges, and proactively refining workflows.Elevate standards for code organization, packaging, and engineering best practices.What We Are Looking For:Preferred QualificationsSolid foundation in software engineering principles.Genuine interest in developer experience and best practices for code organization.Effective communicator, adept at collaborating with teammates to understand their requirements.Proactive mindset—identifies issues and implements solutions.Local to San Francisco (this role requires in-office attendance).Ideal Background (in order of importance)Open source contributor—experience with tools similar to Ruff, uv, or other developer-centric projects.Experience in build systems and CI—has developed or overseen build systems, CI pipelines, or developer tools on a large scale.Data pipeline experience—understanding of optimizing data workflows and data handling.

About Liquid AIOriginating from MIT CSAIL, Liquid AI specializes in the development of general-purpose AI systems designed to operate seamlessly across various platforms, including data center accelerators and on-device hardware. Our focus is on delivering low latency, efficient memory usage, privacy, and reliability. We collaborate with organizations in diverse sectors such as consumer electronics, automotive, life sciences, and financial services. As we experience rapid growth, we seek outstanding talent to join our mission.The OpportunityThe Training Infrastructure team is at the forefront of building the distributed systems that empower our next-generation Liquid Foundation Models. As our operations expand, we aim to innovate, implement, and enhance the infrastructure crucial for large-scale training.This role is centered around high ownership of training systems, emphasizing runtime, performance, and reliability rather than a typical platform or SRE function. You will collaborate within a small, agile team, creating vital systems from the ground up instead of working with pre-existing infrastructure.While San Francisco and Boston are preferred, we are open to other locations.What We're Looking ForWe are seeking an individual who:Embraces the complexity of distributed systems: Our team is dedicated to maintaining stability during extensive training runs, troubleshooting training failures across GPU clusters, and enhancing overall performance.Is passionate about building: We value team members who take pride in developing robust, efficient, and reliable infrastructure.Excels in uncertain environments: Our systems are designed to support evolving model architectures. You will be making decisions based on incomplete information and rapidly iterating.Aligns with team goals and delivers results: The best engineers on our team align with collective priorities while providing data-driven feedback when challenges arise.The WorkDesign and develop core systems that ensure quick and reliable large training runs.Create scalable distributed training infrastructure for GPU clusters.Implement and refine parallelism and sharding strategies for evolving architectures.Optimize distributed efficiency through topology-aware collectives, communication/compute overlap, and straggler mitigation.Develop data loading systems to eliminate I/O bottlenecks for multimodal datasets.

At Catalog, we are pioneering the commerce infrastructure for AI—creating the essential framework that enables digital agents to not only explore the web but also comprehend, analyze, and engage with products. Our innovations drive the future of AI-driven shopping experiences, fundamentally transforming how consumers discover and purchase items online.Role OverviewAs a Technical Staff Member, you will be instrumental in developing core systems, shaping our engineering culture, and transitioning our vision from prototype to a robust platform. This role requires full-stack expertise and a commitment to owning and resolving challenges from start to finish.Who You AreYou have experience creating beloved and trusted products from the ground up.You combine technical proficiency with a keen product sense and data-driven intuition.You are well-versed in AI technologies.You prioritize speed, write clean code, and ensure thorough instrumentation.You seek a high level of ownership within a small, talent-rich team based in San Francisco.Challenges You Will TackleDevelop and deploy agentic-search APIs that deliver structured and real-time product data in milliseconds.Build checkout systems enabling agents to conduct transactions with any merchant.Create an embeddings and retrieval layer that optimizes recall, precision, and cost efficiency.Establish a product graph and ranking pipeline that adapts based on actual user outcomes.Preferred QualificationsProven experience shipping data-centric products in a live environment.Experience with recommendation systems or information retrieval methodologies.Familiarity with API development, search indexing, and data pipeline construction.Our Work CultureWe operate with a small, high-trust, and highly motivated team, fostering an environment of in-person collaboration in North Beach, San Francisco. Our process involves debate, decision-making, and execution.If your profile aligns with our needs, we will contact you to arrange 2-3 brief technical interviews, followed by an onsite meeting in our office where you will collaborate on a small project, exchange ideas, and meet the team.

At Composio, we are developing advanced infrastructure that enables agents to seamlessly interact with essential work tools such as GitHub, Gmail, Notion, Salesforce, and more. Our dedicated team of engineers is committed to tackling challenges ranging from contextual understanding to search functionalities, ensuring we provide an exceptional bridge between your agents and their tools.Having secured a $25M Series A funding from Lightspeed, alongside prominent angel investors like Guillermo Rauch (CEO of Vercel), Dharmesh Shah (CTO of HubSpot), and Gokul Rajaram, we have experienced remarkable growth, tripling our ARR at the start of this year. Our clientele includes notable names from Y Combinator cohorts to Wabi, Glean, Zoom, and beyond.Your RoleEnhance the experience of teams utilizing our platform by refining our core APIs and SDK.Create intuitive interfaces for both frontend and SDK applications.Take ownership of product development from concept through to production.Collaborate closely with customers to cultivate their loyalty while enhancing the product.Craft clear and concise documentation.

About TierZero TierZero helps engineering teams use AI to build and ship code more efficiently. The platform targets the bottleneck of human speed in production, giving teams tools for faster incident response, better operational visibility, and shared knowledge. TierZero is backed by $7M in funding from investors including Accel and SV Angel. Companies like Discord, Drata, and Framer trust TierZero to strengthen their infrastructure for AI-driven engineering. Role Overview: Founding Member of Technical Staff This is an on-site role based at TierZero’s San Francisco headquarters, with three days a week in the office. As a founding member, direct collaboration with the CEO, CTO, and early customers shapes the direction of both product and systems. The work spans hands-on development and close engagement with users and leadership. What You Will Do Design and build intelligent AI systems to analyze large volumes of unstructured data. Deliver full-stack features based on real user feedback. Improve the product experience so AI agents are both reliable and easy for engineers to use. Develop systems that automatically evaluate LLM outputs and advance agentic reasoning using self-play and feedback loops. Create machine learning pipelines, including data ingestion, feature generation, embedding stores, retrieval-augmented generation (RAG), vector search, and graph databases. Prototype with open-source and new LLMs, comparing their strengths and weaknesses. Build scalable infrastructure for long-running, multi-step agents, with attention to memory, state, and asynchronous workflows. What We Look For Over five years of relevant professional or open-source experience. Comfort working in environments with uncertainty and evolving challenges. Strong product focus and a drive for customer satisfaction. Interest in large language models (LLMs), Model Control Planes (MCPs), cloud infrastructure, and observability tools. Previous startup experience is a plus. Location This position is based in San Francisco. Expect to work on-site three days per week at TierZero’s HQ.

TierZero builds tools that help engineering teams deliver and manage code efficiently. The platform enables quicker incident response, clearer operational visibility, and shared knowledge among engineers. Backed by $7 million from investors like Accel and SV Angel, TierZero supports clients such as Discord, Drata, and Framer as they strengthen infrastructure for AI-driven work. This in-person role is based at TierZero's San Francisco headquarters, with a hybrid schedule requiring three days onsite each week. As a founding member of the technical staff, work directly with the CEO, CTO, and customers to influence the direction of TierZero’s core products and systems. The position calls for flexibility as priorities shift and close collaboration across the company. What you will do Design and develop AI systems that handle large volumes of unstructured data. Build full-stack product features, informed by direct feedback from users. Enhance the product so agents are intelligent, reliable, and easy for engineers to use. Create systems to automatically evaluate outputs from large language models and improve agentic reasoning through self-play and feedback. Construct machine learning pipelines, including data ingestion, feature creation, embedding stores, retrieval-augmented generation (RAG) pipelines, vector search, and graph databases. Experiment with open-source and emerging large language models to compare different approaches. Develop scalable infrastructure for long-running, multi-step agents, including memory, state management, and asynchronous workflows. Requirements Interest in working with large language models, managed cloud platforms, cloud infrastructure, and observability tools. At least 5 years of professional experience or significant open-source contributions. Comfort with shifting priorities and tackling new technical problems. Strong product focus and commitment to customer outcomes. Openness to learning from a team with a track record of delivering over $10 billion in value. Ability to work onsite in San Francisco three days per week. Bonus: Experience in a startup setting and familiarity with startup dynamics.

Our VisionAt ReflectionAI, we strive to create open superintelligence and ensure its accessibility for everyone.Our team is dedicated to developing open weight models for individuals, organizations, and even nations. Our collective expertise comes from leading AI institutions such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic, and more.Role OverviewConduct research and develop solutions focusing on algorithms, scaling laws, data processing, optimizers, and model architecture.Design and execute scientific experiments to enhance our understanding of scaling large language models and improving data efficiency.Apply cutting-edge techniques from the deep learning literature to our projects.Independently lead small research initiatives while collaborating on larger projects.Enhance our training infrastructure for optimal scaling efficiency.Contribute across the entire technology stack, from low-level optimizations to high-level model design.Your ProfilePossess a graduate degree (MS or PhD) in Computer Science, Machine Learning, or a related field.Demonstrate strong software engineering skills with experience in large-scale systems development.Have prior experience with large-scale ETL processes and preparing training data.Possess a deep understanding of large-scale machine learning, specifically regarding language models, distributed training, and scaling.Be proficient in Python and familiar with deep learning frameworks, preferably PyTorch.Effectively navigate the trade-offs between research goals and practical engineering challenges.Excel in a fast-paced, high-agency startup culture with a proactive approach.Exhibit strong communication skills and a collaborative mindset.Show a passion for pushing the boundaries of intelligence.What We Provide:We believe that building truly open superintelligence starts with a solid foundation. Joining ReflectionAI means being part of a tightly-knit, highly talented team, where you will help shape our future and redefine the landscape of open foundational models.

Join our dynamic team at Adyen as a Technical Staff Member in San Francisco! We are seeking innovative minds passionate about technology and problem-solving. In this role, you will collaborate with cross-functional teams to craft solutions that enhance our services and improve customer experiences.

tierzero is looking for a Founding Member of Technical Staff to help shape the direction of its technology from the ground up. This role is based at the company's San Francisco headquarters. Role overview As an early technical hire, you will work closely with engineers and product managers to build new products and features. The work centers on designing, coding, and delivering software solutions that address client needs and support tierzero's growth. Impact Contributions in this role will directly influence the company's future. The team values initiative and hands-on problem solving, giving each member a chance to make a visible difference in how the company evolves. Collaboration This position involves regular collaboration with a small, focused team. Input and ideas from every member help guide product direction and technical decisions.

About tierzero tierzero helps engineering teams build and deploy code with greater speed and operational clarity in an AI-driven world. The company focuses on improving incident response, operational visibility, and knowledge sharing for engineers. Backed by $7 million in funding from investors like Accel and SV Angel, tierzero supports large-scale systems for clients such as Discord, Drata, and Framer. Role Overview: Founding Member of Technical Staff This role is based at tierzero's San Francisco headquarters. In-person work is required three days a week. As a founding member of the technical team, you will help design and build core products and systems from the ground up. Collaboration is central: expect to work closely with the CEO, CTO, and customers. Projects span a wide range of technical challenges and product areas. What You Will Do Design and implement intelligent AI systems that process and reason over large volumes of unstructured data. Develop full-stack features, incorporating direct feedback from users. Improve the product experience so intelligent agents are practical and reliable for engineers. Create systems that automatically evaluate LLM outputs and refine agent reasoning using self-play and feedback loops. Build machine learning pipelines covering data ingestion, feature generation, embedding stores, RAG pipelines, vector search, and graph databases. Prototype and experiment with open-source and advanced LLMs to weigh different approaches. Set up scalable infrastructure for long-running, multi-step agents, including memory management, state handling, and asynchronous workflows. What We Look For At least 5 years of professional or open-source experience in a relevant technical field. Comfort working in a setting that changes and evolves quickly. Strong product focus and an understanding of customer needs. Interest in LLMs, MCPs, cloud infrastructure, and observability tools. Ability to learn from and collaborate with engineers who have delivered over $10 billion in value. Commitment to working onsite in San Francisco three days per week. Startup experience is a plus.

tierzero seeks a Founding Member of Technical Staff to play a key role in building the company’s technology from the earliest stages. This position is based at the San Francisco headquarters and offers the chance to collaborate directly with founders and engineers. Role overview As an early team member, you will help design and develop new products and systems. The work involves close collaboration with others in the office, shaping both the technical direction and the culture of the engineering team. What you will do Develop core technology in partnership with founders and engineers Contribute ideas and code that guide the evolution of tierzero’s products Help define engineering standards and establish best practices Location This position is based onsite at the San Francisco HQ.

Overview: Due to the increasing market demand and a robust six-month product roadmap, Listen Labs is expanding its engineering team. We seek a technically adept individual (our team includes three IOI medalists) who is eager to contribute to a product that is revolutionizing corporate decision-making. If you are passionate about solving intricate problems from start to finish, we invite you to connect with us.About Listen LabsListen Labs is an innovative AI-driven research platform that empowers teams to swiftly extract insights from customer interviews in hours rather than months. Our technology enables clients to analyze conversations, identify recurring themes, and expedite informed product decisions.Company Highlights:Exceptional Team: Composed of seasoned entrepreneurs (with prior AI exits), co-founders, and experts from leading firms such as Jane Street, Twitter, Stripe, Affirm, Bain, Goldman Sachs, and more, our team is built on a foundation of excellence.Rapid Growth: We are a dynamic team of 40, supported by Sequoia, achieving a remarkable growth trajectory from $0 to $14 million run-rate in less than a year. We prioritize speed, craftsmanship, and collaboration with individuals who embrace ownership.Impressive Traction: We have seen rapid growth across various sectors, securing enterprise clients such as Google, Microsoft, Nestlé, and P&G.Outstanding Performance: Our industry-leading win rate is a direct result of our uniquely differentiated product.Market Validation: We consistently attract customers across every segment, often landing six-figure deals that lead to quick expansions.Viral Product: Our interviews are shared with tens of thousands of viewers, driving product-led growth, organic expansion, and daily inquiries from Fortune 500 companies.Technical Challenges:Research Agent Development: Unlike traditional software purchases, hiring McKinsey involves gaining insights and execution expertise. We are building Listen Labs with that mindset — an AI agent that understands our platform and best research practices, assisting users in project setup, interview execution, and response analysis.Human Database Creation: A core value proposition is our capability to connect users with specific demographics. We are developing a database of millions of individuals, continually enhancing our understanding of user needs as they engage with Listen Labs.

Technical Staff MemberMirendil is a pioneering technology company dedicated to addressing fundamental challenges that propel significant advancements in science and technology. Our primary mission is to democratize access to cutting-edge AI research and development across various scientific fields. We believe that accelerating scientific discovery is one of the most impactful ways to enhance humanity's future, with AI playing a crucial role in achieving this vision.We are in the process of establishing a leading AI research company, developing our own models from the ground up. Our focus encompasses model training, reinforcement learning, reasoning systems, and the infrastructure necessary for large-scale experiments. Our team comprises accomplished researchers and engineers from esteemed organizations such as Anthropic, Google DeepMind, xAI, OpenAI, Microsoft, Apple, and MIT.Position OverviewWe are seeking skilled engineers and researchers to join us as Members of Technical Staff.This role is designed to be flexible and open-ended. Depending on your expertise and interests, you may engage in:Enhancing and training advanced AI modelsDeveloping reinforcement learning and reasoning systemsBuilding infrastructure for extensive experimental projectsCreating systems to automate or expedite research workflowsIf you are passionate about tackling ambitious challenges at the crossroads of AI, research, and scientific innovation, we would love to connect with you.

At teameigen, we are a dynamic group of innovators, engineers, and storytellers, supported by renowned venture capitalists and the visionaries behind some of the world’s most cherished consumer products, as well as influential figures from film, music, and television.We seek passionate builders with a keen sense of product development to advance applied emotional intelligence and create the technological frameworks that will define consumer technology in the next decade.As a member of our technical staff, you will:Independently tackle complex and ambiguous challenges from start to finish.Engage across the entire technology stack with a product-first mindset rather than a tech-centric approach.Collaborate with writers, artists, and other creatives to enhance the emotional and aesthetic experience of our product.Demonstrate relentless urgency and a strong work ethic in all projects.

As a Technical Staff Member specializing in Machine Learning, you will:Engage in the complete development lifecycle of innovative large-scale deep learning models.Curate datasets, architect solutions, implement algorithms, and train and assess models to enhance our offerings.Work collaboratively with engineers and researchers to convert groundbreaking research into real-world applications.Join us at a pivotal time, take on diverse roles, and contribute to building transformative products from the ground up!

Role Overview Intuitive Surgical, Inc. is hiring a Staff Quality Engineer in San Francisco. This role focuses on maintaining quality standards for robotic-assisted surgical systems. The position works closely with teams across the company to support quality assurance and uphold compliance with industry regulations. Key Responsibilities Maintain and improve quality standards for surgical products Collaborate with cross-functional teams to support quality assurance activities Ensure compliance with relevant industry regulations Contribute to initiatives that drive continuous improvement in product quality and operations

At Inferact, we are on a mission to establish vLLM as the premier AI inference engine, revolutionizing AI progress by making inference both more accessible and efficient. Our founding team consists of the original creators and key maintainers of vLLM, positioning us uniquely at the nexus of cutting-edge models and advanced hardware.Role OverviewWe are seeking a passionate inference runtime engineer eager to explore and expand the frontiers of LLM and diffusion model serving. As models evolve and grow in complexity with new architectures like mixture-of-experts and multimodal designs, the demand for innovative solutions in our inference engine intensifies. This role places you at the heart of vLLM, where you will enhance model execution across a variety of hardware platforms and architectures. Your contributions will have a direct influence on the future of AI inference.