Post-Training Technical Staff Member at Liquid AI | San Francisco

Join Perplexity as a pioneering Technical Staff Member in one of the most innovative engineering roles in the AI sector. Collaborate closely with our senior leadership to drive a diverse array of strategic technology initiatives that encompass AI policy, law, operations, and corporate affairs.Reporting directly to the VP of Global Affairs & Deputy CTO, you will gain insight into the critical policy matters shaping the AI landscape. This role offers a holistic perspective on the operations and decision-making processes of leading AI companies and their engagement with society.If you are passionate about blending technical proficiency with interests in law, policy, and corporate matters, you'll find your place here. Your contributions will challenge the status quo, supported by a team of mentors dedicated to fostering your growth and development.Responsibilities:This role demands an interdisciplinary approach firmly anchored in engineering principles. Your daily tasks may include:Utilizing AI agents to investigate critical policy and regulatory challenges relevant to Perplexity.Developing automated systems for the collection, prioritization, and patenting of Perplexity's innovations, in coordination with our AI researchers and IP attorneys.Collaborating with our Legal team and external counsel on advanced litigation issues in U.S. federal courts.Designing privacy and compliance frameworks that grow alongside our expanding suite of pioneering AI products.Assisting in regulatory submissions and responses that necessitate a thorough understanding of AI technologies, Perplexity’s systems, and the wider policy context.Working with our People team to deploy software solutions for recruitment, labor compliance, and performance evaluation.Engaging in discussions with Capitol Hill, executive branch officials, international stakeholders, and civil society as a subject-matter expert on AI technology and policy.This overview captures just a fraction of your potential activities; each day will be unique, providing you with opportunities across various domains within our organization.

Overview: Join Listen Labs as we respond to a surge in market demand with an ambitious 6-month product roadmap. We are expanding our engineering team and are on the lookout for a highly skilled technical expert (our current team includes three IOI medalists) who is eager to build a transformative product that reshapes decision-making for businesses. If you have a passion for solving intricate problems from start to finish, we want to connect with you.About Listen LabsListen Labs is an AI-driven research platform designed to help teams quickly extract insights from customer interviews in a matter of hours rather than months. We empower our clients by enabling them to analyze conversations, identify key themes, and make faster, more informed product decisions.Why Work with Us?Exceptional Team: Founded by seasoned entrepreneurs with a successful AI exit, along with talent from renowned companies such as Jane Street, Twitter, Stripe, Affirm, Bain, and Goldman Sachs, our team boasts impressive credentials including IOI and ICPC backgrounds.Rapid Growth: As a 40-person team backed by Sequoia Capital, we have achieved a remarkable growth trajectory, scaling from $0 to a $14 million run-rate in less than a year. We prioritize craftsmanship and thrive on collaboration with individuals who take ownership.Impressive Traction: We are experiencing rapid growth across various sectors, securing enterprise clients such as Google, Microsoft, Nestlé, and Procter & Gamble.Proven Performance: We maintain an industry-leading win rate driven by our uniquely differentiated product.Market Validation: We consistently attract customers from diverse segments, achieving six-figure contracts that facilitate quick expansions.Viral Product: Our interviews reach tens of thousands of viewers, promoting product-led growth, organic expansion, and daily interest from Fortune 500 companies.Technical Challenges Await:Research Agent Development:Unlike traditional software purchases, hiring McKinsey offers valuable opinions, expertise, and execution. We aim to provide users with an AI agent that possesses complete knowledge about our platform and best research practices, assisting them in project setup, interview conduction, and response analysis.Human Database Creation:One of our core offerings is the ability to identify target users effectively (e.g., "power users of ChatGPT and Excel"). We are in the process of building a comprehensive database that connects users with the insights they need.

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.

About Liquid AIOriginating from MIT CSAIL, Liquid AI specializes in creating versatile AI systems that operate efficiently across various platforms, from data center accelerators to on-device hardware, focusing on low latency, minimal memory consumption, privacy, and dependability. Our collaborations extend across industries including consumer electronics, automotive, life sciences, and financial services. As we undergo rapid expansion, we are on the lookout for outstanding individuals to join our journey.The OpportunityThe Vision-Language Models (VLM) team is dedicated to developing cutting-edge vision-language models that function seamlessly on devices, adhering to stringent latency and memory requirements without compromising quality. Having already launched four premier models, we are excited about what lies ahead.This team is responsible for the complete VLM pipeline, encompassing research on novel architectures, training algorithms, data curation, evaluation, and deployment. You will be part of a dedicated, hands-on team that directly engages with models and works closely with our pretraining, post-training, and infrastructure teams. Your success will be gauged by the performance of the models we deliver.

At Stuut AI, we are revolutionizing accounts receivable for B2B companies, enhancing collections to be smarter and more efficient. Our platform is increasingly being adopted by finance teams in various sectors, including industrials, chemicals, and manufacturing, with clients ranging from Fortune 10 enterprises to growing midmarket firms. Our innovative approach is supported by esteemed investors such as Andreessen Horowitz, Khosla Ventures, Activant, 1984 Ventures, and Page One.Position OverviewWe are seeking a dedicated Technical Staff Member focused on Internal AI Tooling. This pivotal role will involve constructing the foundational systems that allow Stuut to scale effectively. Your primary responsibility will be to design and implement internal infrastructures, automation, and AI-driven workflows to enhance operational efficiency across various departments, starting with marketing and extending to sales, operations, and product development.This is a significant role for a proactive individual who thrives on transforming manual or disjointed processes into scalable systems. Collaboration with leadership and cross-functional teams will be essential as you design AI agents, automation pipelines, and internal tools that streamline operations and unlock new capabilities.We are transitioning to an agent-first model, not only in our products but also in our operational approach. This role is central to that evolution.

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.

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!

About UsAt Parallel, we redefine web infrastructure to empower businesses across various sectors including sales, marketing, insurance, and coding. Our innovative products enable the creation of top-tier AI agents, providing them with flexible and robust programmatic access to the web.Having secured $130 million in funding from prominent investors like Kleiner Perkins, Index Ventures, Spark Capital, Khosla Ventures, First Round, and Terrain, we are on a mission to construct the web tailored for AI applications. We are assembling an elite team of engineers, designers, marketers, sellers, researchers, and operational experts to realize this vision.Job Role: As a member of our research team, your primary objective will be to explore methods to train and scale a model capable of serving a comprehensive web index.Your Profile: You possess a profound understanding of modern AI models and training methodologies. You enjoy engaging in discussions about the convergence of search algorithms, recommendation systems, and transformer models. You are passionate about ensuring your research translates into practical applications that impact millions.Life at ParallelOur team operates in a fully in-person environment, collaborating between our headquarters in Palo Alto and our San Francisco office. We maintain a flat organizational structure that values talent and is committed to tackling both technical and creative challenges.We are looking for individuals who are equally passionate about leveraging science, creativity, and consistency to address significant and complex challenges, leading to substantial outcomes. Our core values include:Own Customer Impact: We take responsibility for delivering real-world results for our clients.Obsess Over Craft: We believe in perfecting every detail, as quality compounds over time.Accelerate Change: We prioritize swift shipping, rapid adaptation, and the implementation of pioneering ideas.Create Win-Wins: We strive to transform trade-offs into advantages.Make High-Conviction Bets: We embrace experimentation, learning from failures to achieve extraordinary successes.Compensation & BenefitsCompetitive salaryGenerous equity optionsVisa sponsorship available401K retirement plansDaily lunches & office snacksDinner provided at the officeUnlimited vacation policyCaltrain pass reimbursement

About Liquid AIOriginating from the prestigious MIT CSAIL, Liquid AI crafts cutting-edge, general-purpose AI systems designed for optimal efficiency across a variety of platforms, from data center accelerators to edge devices. Our solutions prioritize low latency, minimal memory requirements, privacy, and reliability. We collaborate with industry leaders in consumer electronics, automotive, life sciences, and financial services, and as we expand rapidly, we are looking for exceptional talent to join our journey.The OpportunityJoin us at the exciting crossroads of advanced foundation models and the open-source community. In this pivotal role, you will oversee developer relations and community engagement, influencing how our models are adopted, documented, and integrated throughout the AI ecosystem. This unique position allows you to balance impactful community work with essential technical contributions, giving you the chance to shape how our models are represented and utilized by developers worldwide. If you are passionate about excellent documentation, enhancing developer experience, and democratizing access to powerful AI models, this is your chance to influence the future of open-source AI.What We're Looking ForWe seek a proactive individual who:Takes ownership: Manages open-source partnerships from initial outreach to ongoing collaboration.Thinks community-first: Integrates documentation, tutorials, integrations, and support into a seamless developer experience.Is pragmatic: Focuses on developer adoption and partner success rather than superficial metrics.Communicates clearly: Bridges the gap between technical teams and external partners, representing Liquid's interests while fostering genuine relationships.The WorkServe as the primary liaison for open-source partners.Assist in model releases with both marketing and technical content.Create tutorials, articles, and guides on training and utilizing our foundation models.Enhance and maintain LFM documentation for clarity and thoroughness.Collect community feedback and communicate insights to internal teams.

Join Reka as a Member of the Technical Staff in Applied AI!Leverage cutting-edge AI models to tackle intricate real-world challenges.Engage in close collaboration with researchers and fellow team members to explore the latest developments in AI and ML.Partner with our customers to seamlessly integrate our innovative models into their existing technology frameworks.Drive business success with a strong sense of product ownership and accountability.Be part of a pioneering team in a rapidly growing environment, taking on diverse roles.

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.

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.

At Krew, we are dedicated to revolutionizing the credit-servicing landscape with cutting-edge AI-driven solutions. Our world-class team is supported by prominent investors, including Long Journey Ventures, Ryan Hoover, Charlie Songhurst, and Michael Jones. Our diverse team brings expertise from renowned organizations such as Figure Robotics, Optiver, Bain, and the United Nations, comprising engineers and researchers from prestigious institutions like UChicago and Oxford. Our innovative omnichannel agents are currently assisting over 100,000 consumers on their journey toward financial well-being. We aspire to address over $1 trillion in consumer delinquencies globally through a compassionate and human-centric approach to financial wellness.

At Tzafon, we are pioneering the development of scalable computing systems and pushing the boundaries of machine intelligence with our foundation model lab. Located in vibrant cities such as San Francisco, Zurich, and Tel Aviv, we have successfully secured over $12 million in funding to fuel our mission of expanding the horizons of AI technology.Our dynamic team comprises engineers and scientists with extensive expertise in machine learning infrastructure and research. Founded by IOI and IMO medalists, PhDs, and seasoned professionals from top tech firms, we specialize in training advanced models and constructing robust infrastructures to automate tasks across various real-world scenarios.In this role, you will collaborate closely with our product and post-training teams to deploy Large Action Models that drive impactful results. Your responsibilities will include building evaluation frameworks, establishing benchmarks, and creating fine-tuning pipelines to ensure optimal model performance.

About tierzero tierzero builds tools that help engineering teams manage production code with stronger incident response, better operational visibility, and collaborative knowledge sharing. Companies like Discord, Drata, and Framer use tierzero to support their infrastructure in an AI-driven landscape. Backed by $7 million from investors including Accel and SV Angel, tierzero is growing quickly from its San Francisco headquarters. Role Overview: Founding Member of Technical Staff This is a hands-on role shaping tierzero’s core product and systems from the ground up. The founding technical team works closely with the CEO, CTO, and early customers to solve real engineering challenges. The position is based in San Francisco, with a hybrid schedule: three days each week in the office. What You’ll Do Design and build intelligent AI systems that process large volumes of unstructured data Deliver full-stack features informed by real-time user feedback Improve usability so AI agents are both effective and trustworthy for engineers Develop systems for automated evaluation of LLM outputs, including feedback loops and self-play Construct machine learning pipelines for data ingestion, feature generation, embedding storage, retrieval-augmented generation (RAG), vector search, and graph databases Prototype with open-source LLMs to understand their strengths and weaknesses Create scalable infrastructure for complex, multi-step agents, focusing on memory, state management, and asynchronous workflows Who We’re Looking For 5+ years of professional experience or significant open-source contributions Interest in LLMs, MCPs, cloud infrastructure, and observability tools Comfort working in changing, ambiguous situations Product-focused and customer-first mindset Experience learning from and collaborating with engineers from diverse backgrounds Bonus: Previous experience in a startup setting Work Location Hybrid schedule: three days per week in-person at the San Francisco HQ.

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 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 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.