Data Quality Engineer - Member of Technical Staff (Post-training)

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.

About Liquid AIFounded as a spin-off from MIT CSAIL, Liquid AI specializes in the development of versatile artificial intelligence systems optimized for performance across various deployment environments, ranging from data center accelerators to on-device hardware. Our focus on low latency, minimal memory consumption, privacy, and reliability allows us to partner effectively with enterprises in sectors such as consumer electronics, automotive, life sciences, and financial services. As we experience rapid growth, we are eager to welcome talented individuals who can contribute to our mission.The OpportunityThis unique position places you at the forefront of advanced foundation models and their practical applications. You will oversee post-training projects from start to finish for some of the world’s leading enterprises, while also playing a vital role in the ongoing development of Liquid’s core models.In this role, you will not have to choose between impactful customer work and foundational development; instead, you will enjoy deep involvement in both. You will have significant influence over how models are adapted, assessed, and deployed, directly contributing to the enhancement of Liquid’s post-training capabilities.If you are passionate about data integrity, evaluation processes, and ensuring that models perform effectively in real-world scenarios, this is your chance to redefine the standards of applied AI at a foundation-model company.What We're Looking ForWe seek an individual who:Takes ownership: You will lead post-training initiatives from customer requirements to delivery and evaluation.Thinks end-to-end: You will connect the dots across data generation, training, alignment, and evaluation as a cohesive system.Is pragmatic: You prioritize model quality and customer satisfaction over theoretical publications.Communicates clearly: You can interpret customer needs and effectively communicate with internal technical teams, providing constructive feedback when necessary.The WorkServe as the technical lead for post-training engagements with enterprise clients.Translate client requirements into actionable post-training specifications and workflows.Design and implement data generation, filtering, and quality assessment methodologies.Conduct supervised fine-tuning, preference alignment, and reinforcement learning processes.Create task-specific evaluations, analyze outcomes, and integrate insights back into core post-training workflows.

Our MissionAt Reflection AI, our goal is to create open superintelligence and ensure its accessibility for everyone.We are pioneering open weight models for various users, including individuals, enterprises, and even nation-states. Our talented team comprises AI researchers and industry veterans from leading organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, and Anthropic.Role OverviewDevelop systems that convert robust pre-trained models into aligned and versatile agents.Lead research and engineering efforts to advance post-training practices, focusing on data curation and large-scale optimization.Create data generation frameworks, reward models, reinforcement learning algorithms, and techniques for inference-time scaling.Collaborate with both pre-training and post-training teams to achieve significant enhancements in model capabilities.Help refine our understanding of how large models learn to reason, follow instructions, and evolve through reinforcement learning.Your ProfileSolid grasp of machine learning principles with hands-on experience in large-scale LLM training.Proficient engineering skills, with the ability to navigate intricate ML codebases and distributed systems.Experience in enhancing model performance through data, reward modeling, or reinforcement learning techniques.Track record of leading ambitious research or engineering projects resulting in measurable improvements.Thrives in a dynamic, high-agency startup atmosphere; oriented towards action and clarity in execution.Ability to work seamlessly across research and infrastructure boundaries.Excellent communication skills and a collaborative mindset.Driven by a passion for pushing the boundaries of intelligence.What We Provide:At Reflection AI, we believe that to truly build open superintelligence, it must be rooted in a strong foundation. By joining us, you will contribute to building from the ground up within a compact, highly skilled team. Together, we will shape the future of our company and the landscape of open foundational models.We aim for you to accomplish the most impactful work of your career, with the assurance that you and your loved ones are well-supported.

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.

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.

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.

Join Our TeamAt Liquid AI, we are not just creating AI models; we are revolutionizing the very fabric of intelligence. Originating from MIT, our objective is to develop efficient AI systems across all scales. Our Liquid Foundation Models (LFMs) excel in environments where others falter—on-device, at the edge, and under real-time constraints. We are not simply refining existing concepts; we are pioneering the future of AI.We recognize that exceptional talent drives remarkable technology. The Liquid team is a collective of elite engineers, researchers, and innovators dedicated to crafting the next generation of AI solutions. Whether you are designing model architectures, enhancing our development platforms, or facilitating enterprise integrations, your contributions will significantly influence the evolution of intelligent systems.While San Francisco and Boston are preferred locations, we welcome applicants from other regions within the United States.

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.

Join our innovative team at liquid-ai as a Member of the Technical Staff specializing in audio applications. As a post-training role, you will have the opportunity to apply your knowledge in cutting-edge audio technologies, contributing to the development of advanced machine learning solutions.This position is ideal for individuals who are eager to work in a collaborative environment and are passionate about audio technology and its applications in artificial intelligence.

Join Liquid AI as a Technical Staff Member specializing in Applied Vision. In this dynamic role, you will leverage cutting-edge technology to develop innovative solutions and enhance our product offerings. This position is ideal for recent graduates with a passion for technology and a desire to make a meaningful impact in the field of artificial intelligence.

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.

Join Baseten as a Post-Training Research Engineer and contribute to groundbreaking advancements in machine learning and AI. In this role, you will leverage your engineering skills to analyze and enhance models post-training, ensuring optimal performance and efficiency.

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.

OpenAI is hiring a Software Engineer for Post-Training Research in San Francisco. This position centers on improving the performance and capabilities of advanced machine learning models after their initial training phase. Role overview Work closely with a skilled team to explore new ways of strengthening AI systems. The focus is on researching and developing methods that push the boundaries of what these models can achieve once training is complete. Collaboration Expect to contribute to ongoing research efforts and share insights with colleagues who are passionate about advancing AI. Teamwork and knowledge exchange are key parts of this role. Location This position is based in San Francisco.

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.

Advancing Self-Improving SuperintelligenceAt Letta, we are on a mission to revolutionize artificial intelligence by creating self-improving agents that learn and adapt like humans. Unlike current AI systems that are often rigid and brittle, our innovative approach aims to build adaptable AI that continually evolves through experience.Founded by the visionaries behind MemGPT at UC Berkeley's Sky Computing Lab, the birthplace of Spark and Ray, we are backed by notable figures in AI infrastructure, including Jeff Dean and Clem Delangue. Our agents are already enhancing production systems for industry leaders such as 11x and Bilt Rewards, continually learning and improving in real-time.Join our elite team of researchers and engineers dedicated to tackling AI's most significant challenges: creating machines that can reason, remember, and learn as humans do.This position requires in-person attendance (no hybrid options) at our downtown San Francisco office, five days a week.

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.