ML/AI Research Engineer - Founding Team at Agentic AI Lab

ML/AI Research Engineer - Founding Team at Agentic AI LabLocation: San Francisco Bay AreaType: Full-TimeCompensation: Competitive salary + meaningful equity (founding tier)At fabrion, backed by 8VC, we are assembling a top-tier team dedicated to addressing one of the most pressing infrastructure challenges in the industry.About the RoleJoin us in shaping the…

ML Ops Engineer — Agentic AI Lab (Founding Team)Location: San Francisco Bay AreaType: Full-TimeCompensation: Competitive salary + meaningful equity (founding tier)At fabrion, supported by 8VC, we are assembling a premier team to address one of the industry's most significant infrastructure challenges.About the RoleJoin our AI Lab as we advance the future of intelligent infrastructure through pioneering open-source LLMs, agent-native pipelines, retrieval-augmented generation (RAG), and knowledge-graph-grounded models. We seek an ML Ops Engineer who will serve as the vital link between ML research and production systems, taking charge of automating the model training, deployment, versioning, and observability pipelines that empower our agents and AI data fabric.In this role, you will engage in compute orchestration, GPU infrastructure management, fine-tuned model lifecycle stewardship, and ensure model governance and security.Key ResponsibilitiesDesign and maintain secure, scalable, and automated pipelines for:LLM fine-tuning, SFT, LoRA, RLHF, and DPO trainingRAG embedding pipelines with real-time updatesModel conversion, quantization, and inference deploymentOversee hybrid compute infrastructure (cloud, on-premises, GPU clusters) for training and inference workloads utilizing Kubernetes, Ray, and TerraformContainerize models and agents using Docker, ensuring reproducible builds and CI/CD through GitHub Actions or ArgoCDEstablish and enforce model governance, including versioning, metadata management, lineage tracking, reproducibility, and evaluation captureDevelop and manage evaluation and benchmarking frameworks (e.g. OpenLLM-Evals, RAGAS, LangSmith)Integrate with security and access control mechanisms (OPA, ABAC, Keycloak) to implement model policies by tenantImplement observability practices for model latency, token usage, performance metrics, error tracing, and drift detectionAssist in deploying agentic applications using LangGraph, LangChain, and custom inference solutions.

Contribute to a Safer World.At TRM Labs, we specialize in blockchain analytics and AI solutions tailored for law enforcement, national security agencies, financial institutions, and cryptocurrency businesses. Our mission is to empower organizations to detect, investigate, and mitigate crypto-related fraud and financial crime. Our advanced blockchain intelligence and AI platforms provide comprehensive tools for tracing the flow of funds, identifying illicit activities, building strong cases, and creating a cohesive operational picture of potential threats. Trusted by prominent agencies and businesses globally, TRM is dedicated to fostering a safer, more secure world for everyone.As an AI Research Engineer, you will be a vital member of our AI Engineering team, which is dedicated to refining model selection, fine-tuning, and evaluation strategies for large-scale AI systems. In this senior individual contributor role, you will spearhead technical initiatives aimed at enhancing model performance and orchestration, thereby directly influencing the competitiveness of our AI Engineering platform.Your Impact:Design, develop, and take ownership of a production-grade evaluation system that leads to measurable advancements in model accuracy and latency.Lead experimentation processes, fine-tuning efforts, and feedback-driven evaluation loops to continuously optimize models.Enhance the orchestration of AI/ML systems to guarantee scalable, resilient, and high-impact deployments.Raise technical standards through engineering excellence, mentorship, and leadership as a senior individual contributor.Qualifications We Seek:Proven advanced programming skills in Python and SQL, complemented by strong system design abilities.Extensive experience in deploying machine learning/deep learning models in production environments (experience with LLM/GenAI is highly preferred).Solid understanding of experimentation frameworks, evaluation metrics, and ML Ops best practices.Demonstrated capability to manage critical systems end-to-end while effectively collaborating with cross-functional teams.About Our Team:Our AI Engineering team fosters a collaborative and interdependent environment, promoting an inclusive culture where connections go beyond professional interactions. We value diverse perspectives and are looking for individuals who are results-oriented and personable, possessing strong communication, leadership, and teamwork skills, combined with a positive, solutions-focused attitude.As a globally distributed team, members may observe varied time zones, allowing for flexible collaboration.

Role OverviewLocation: San Francisco, CA Work Model: In-officeAbout Effective AIAt Effective AI, we are pioneering the future of work, focusing on sophisticated AI solutions for complex knowledge tasks rather than simple, repetitive functions. Our goal is to develop advanced AI Teammates that excel in intricate workflows and collaborate seamlessly with human professionals. Our initial challenge is to revolutionize the trillion-dollar U.S. Property & Casualty insurance sector, an area rich in data and complexity, ideal for our innovative approach.We have successfully secured $10 million in seed funding from prominent investors including Lightspeed Ventures and Valor Equity Partners.Our passionate team operates out of San Francisco, where we value in-person collaboration to address these pressing challenges.Your ResponsibilitiesAs a Founding Software Engineer, you will be an integral member of our founding team, significantly influencing the design and development of our core product from inception. You will confront critical challenges in agentic AI, crafting Teammates capable of managing essential insurance functions such as underwriting and claims processing.Specifically, you will:Facilitate long-term task completion by creating the foundational architecture for AI agents to plan and execute multi-step processes reliably over prolonged interactions.Develop advanced reasoning functionalities, enabling agents to make informed decisions based on ambiguous or incomplete information, akin to human experts.Create intelligent, tool-utilizing agents capable of selecting and employing a variety of external tools—APIs, databases, web searches, and Excel-based pricing algorithms—to gather information and take decisive actions.Design adaptive and learning systems, equipping our AI Teammates to learn from feedback and adjust to evolving conditions such as regulatory changes or market dynamics.Your ProfileWe seek an innovative and driven builder excited to tackle substantial challenges.You possess a solid foundation in computer science and remarkable problem-solving capabilities, evidenced by impactful projects or previous experience.Your genuine enthusiasm for AI fuels your passion for tackling complex issues.

Join Us at Pylon as a Software Engineer - AI AgentsAt Pylon, we are revolutionizing the B2B post-sales landscape. Our comprehensive platform, driven by conversational data and advanced intelligence, empowers businesses to operate seamlessly in real-time.Supported by notable investors such as a16z, BCV, General Catalyst, and Y Combinator, we proudly serve over 1000 companies, including Linear, Cognition, Modal Labs, and Incident.io. Our inclusion in the Enterprise Tech 30 List shines a light on our impact.With a vast problem domain, we are eager to expand our team of talented software engineers to tackle the exciting challenges ahead. Your contributions will directly influence the development of our innovative solutions.Your RoleDevelop and implement the next generation of AI features at Pylon, swiftly adapting based on user feedback.Enhance the quality and efficiency of existing AI functionalities.Are You the Right Fit?If you prefer coding over meetings and value productivity, you might fit right in.Strong engineering fundamentals and efficient coding skills are essential.Autonomy excites you; you enjoy owning details and managing your projects.Located in San Francisco or willing to relocate? We value in-person collaboration as we cultivate a vibrant team culture.Our tech stack includes React, Golang, GraphQL, and AWS.Join a team of experienced engineers from prestigious companies like Samsara, Affinity, and Airbnb.What We Offer Comprehensive medical, dental, and vision coverage for employees 401(k) retirement plan Commuter benefits Parental leave 14 company holidays plus unlimited PTO Annual offsite retreats Meals and snacks provided at the office Fitness stipend

About Simple AIAt Simple AI, we are pioneering cutting-edge voice AI solutions tailored for enterprises. Our lifelike voice agents empower renowned companies such as DoorDash, xAI, and Omaha Steaks in managing diverse phone operations ranging from customer support to order intake and lead qualification. As we experience rapid revenue growth, we seek a couple of founding software engineers to help us meet current customer demands while developing innovative systems for the future. Our team is passionate about harnessing AI to transform the world, and we operate from our San Francisco office five days a week.Simple AI is proudly supported by top-tier investors and industry leaders, including Y Combinator, Massive Tech Ventures, and prominent figures like Michael Seibel (co-founder of Twitch), Jared Friedman (Scribd), Alexandr Wang (Scale AI), Matt Van Horn (June Oven and Lyft), Suhail Doshi (Mixpanel), JJ Fliegelman (WayUp), and Scott Wu (Cognition).Meet the FoundersThe founders, Catheryn Li and Zach Kamran, previously led software teams at Y Combinator, where they launched numerous products for YC founders, including the co-founder matching site. Cat brings experience from Instagram and Facebook and holds degrees in mathematics and computer science from MIT. Zach studied computer science and statistics at the University of Chicago and led software initiatives at PEAK6.What We ProvideCompetitive salary with significant equity opportunitiesEmployee-friendly equity termsOffice located in San FranciscoComprehensive health, dental, and vision insuranceComplimentary lunch and dinner at the officeFree Uber rides home after 8:30 PMRegular team events and offsite activitiesYour Qualifications4+ years of relevant software engineering experience.Exceptional problem-solving skills and a passion for tackling technical challenges.A customer-centric mindset coupled with strong communication skills and a keen interest in product design and prioritization.Self-motivated with the ability to work independently.A genuine enthusiasm for continual learning and keeping abreast of the latest advancements in AI.

About Uplane (YC F25)At Uplane, we are revolutionizing the advertising industry. Companies are losing billions due to ineffective ads, misaligned landing pages, and suboptimal budget distribution. Uplane addresses these challenges by integrating various agencies, spreadsheets, and isolated tools into a cohesive, self-optimizing AI platform. Our system not only generates advertisements but also crafts corresponding landing pages, optimizes budget allocation across diverse channels, and more. Join us in constructing the AI engine that will redefine how marketing budgets are managed and spent worldwide.About The RoleWe are on the lookout for an innovative and self-motivated AI Software Engineer to become a crucial part of our team in San Francisco. This full-time, on-site position presents an exceptional opportunity to take full ownership of product features from ideation to deployment in a dynamic startup environment.Why Join Us?Be among the pioneering employees of a well-funded startup.Tackle significant challenges in a vast market.Take charge of projects and experience rapid professional growth.Enjoy a culture that is fast-paced, ambitious, enjoyable, and humble.Key ResponsibilitiesCreate AI Systems: Design, develop, and maintain scalable AI solutions with LangGraph and TypeScript for automated marketing campaigns.Data Infrastructure Design: Build the data analytics framework that enables AI agents to enhance their intelligence over time.Architect Robust Systems: Construct and manage efficient database architectures using PostgreSQL and Supabase to ensure data integrity and performance.End-to-End Project Management: Lead projects through all phases, from concept to implementation, deployment, and ongoing support.User-Centric Feature Development: Utilize your product and design insight to create features focused on user needs and market trends.Collaborative Engagement: Work closely with the operations team and clients via Slack and Notion to align technical solutions with user expectations.QualificationsBachelor’s or Master’s degree in Computer Science, Data Science, or a related engineering field, or equivalent practical experience.Proficiency in programming languages such as TypeScript and experience with AI systems is preferred.Strong understanding of database management, particularly with PostgreSQL and Supabase.Ability to collaborate effectively within a team and communicate technical concepts clearly.

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

About Liquid LabsAt Liquid AI, research has always been at the forefront of our mission. Liquid Labs serves as a dedicated internal research accelerator, facilitating groundbreaking advancements in the development of intelligent, personalized, and adaptive machines.Our roots extend back to MIT CSAIL, where pioneering work on Liquid Neural Networks established a new category of efficient sequence-processing architectures. This research laid the groundwork for our Liquid Foundation Models (LFMs), which are scalable, multimodal models designed for real-world applications in resource-constrained settings.In Liquid Labs, we continue this legacy by advancing the realm of efficient, adaptive intelligence through both fundamental research and practical engineering efforts.We collaborate closely with Liquid’s core foundation model and systems teams to turn theoretical concepts into deployable capabilities, setting the stage for a new era of powerful and efficient intelligent systems.About The Role:As a Research Engineer at Liquid Labs, you will be part of a dynamic, high-impact team pushing the boundaries of adaptive intelligence. You will be responsible for designing and implementing innovative architectures, training methodologies, and inference strategies to expand the potential of efficient AI.Your work will blend research and engineering, as you translate scientific concepts into functional systems, publish findings that advance the field, and deploy solutions that redefine what is achievable.While we prefer candidates from San Francisco and Boston, we welcome applications from other locations within the United States.

Role OverviewLocation: San Francisco, CA or Remote (US) Work Model: In-office/RemoteAbout Effective AIAt Effective AI, we are pioneering the future of work by pushing the boundaries of artificial intelligence. We believe that the true potential of AI lies not in automating simple tasks, but in enhancing complex knowledge work that requires critical thinking and expertise. Our mission is to create advanced AI Teammates that excel in navigating intricate workflows and collaborating seamlessly with human professionals. We are initially focusing on the trillion-dollar U.S. Property & Casualty insurance sector, an area rich in data and complex processes, presenting an exciting challenge.Having secured $10 million in seed funding from esteemed investors such as Lightspeed Ventures and Valor Equity Partners, our team is based in San Francisco and thrives on close collaboration to tackle these daunting challenges.Your Role and ResponsibilitiesAs a Founding Frontend Engineer, you will be an integral member of our pioneering team, instrumental in crafting and developing our core product from its inception. You will explore the intersection of AI and human collaboration through data-intensive analytical projects tailored for insurance professionals.Key responsibilities include:Facilitating long-term task execution by establishing essential UX patterns for engaging with multi-turn, multi-tool AI systems.Empowering actuaries and underwriters to process thousands of documents simultaneously by providing them with coding tools and coding agents.Designing and implementing our frontend architecture using contemporary frameworks (React, TypeScript, Tailwind), with a strong emphasis on performance and maintainability.Hands-on involvement with our backend and core agentic platform, all developed in TypeScript.Collaborating closely with design, backend, and machine learning engineers to craft comprehensive user experiences.Rapidly prototyping and iterating on features while balancing speed and quality in a dynamic startup environment.Who You AreWe are in search of an innovative and driven creator eager to take on challenging problems.You possess a genuine passion for AI and thrive on solving ambiguous challenges through first principles thinking.You have extensive experience in developing production-ready web applications.

About Absentia LabsAbsentia Labs is at the forefront of innovation, creating intelligent systems that integrate artificial intelligence, biology, chemistry, and large-scale engineering. Our mission is to convert intricate scientific data into machine intelligence that can reason, generalize, and foster discovery.We tackle the challenges of fragmented, noisy, and interconnected biomedical data, transforming it into a meaningful signal through robust data foundations and well-designed learning systems that are scalable across different modalities, tasks, and uncertainties. This position emphasizes the design and training of such systems.The RoleAs a Senior AI/ML Engineer, you will spearhead the architecture, training, and deployment of large-scale machine learning models that are central to Absentia Labs’ AI initiatives. Your role will bridge model architecture, training systems, and production infrastructure, granting you significant ownership of the technical direction.This position is tailored for engineers experienced in training large models in real-world production settings, who are adept at navigating scale and can analyze both learning dynamics and system constraints.What You’ll DoDesign, train, and evaluate large-scale models, including Large Language Models (LLMs), diffusion models, and Graph Neural Networks (GNNs).Own end-to-end training pipelines, from dataset interfaces and batching strategies to distributed training and checkpointing.Make informed decisions regarding model architecture, objective functions, optimization strategies, and scaling principles.Develop and enhance distributed training systems (data parallelism, model parallelism, sharding, mixed precision).Collaborate closely with data engineers to establish ML-ready datasets and streaming interfaces.Translate vague scientific or product requirements into solid ML solutions.Lead model assessment, ablation, and iteration with a focus on generalization, stability, and reproducibility.Contribute to architectural decisions concerning model serving, inference efficiency, and lifecycle management.Provide technical leadership through design reviews, mentorship, and cross-functional collaboration.Who You AreYou are a senior ML engineer with a holistic approach to models as systems. You comfortably navigate uncertainty, make informed trade-offs between compute, data, and performance, and take ownership of outcomes from research through to deployment.

Join AfterQuery as an AI/ML Research Intern and immerse yourself in groundbreaking artificial intelligence projects. This internship is designed for exceptional undergraduate and master's students eager to collaborate with our research team on advanced reasoning and agentic models. You will have the opportunity to access specialized datasets and work closely with industry experts, contributing to exciting AI research that could lead to co-authored papers and presentations at prestigious AI conferences.We invite students currently enrolled in relevant programs to apply. This role requires a commitment of 10 to 40 hours per week, adaptable to the needs of the company.

Contribute to a Safer World.At TRM Labs, we leverage blockchain analytics and AI innovations to empower law enforcement, national security entities, financial institutions, and cryptocurrency enterprises in identifying, investigating, and thwarting crypto-related fraud and financial misconduct. Our advanced blockchain intelligence and AI solutions facilitate the tracing of fund sources and destinations, recognition of illicit activities, case-building, and the development of a comprehensive threat landscape. We are a trusted partner to prominent organizations globally, dedicated to fostering a safer and more secure environment for all.Our AI Engineering Team is focused on pioneering next-generation AI applications, with a particular emphasis on Large Language Models (LLMs) and agentic systems. Our goal is to create resilient pipelines, high-performance infrastructure, and operational tools that ensure AI systems can be deployed with speed, safety, and scalability.We handle petabyte-scale data pipelines, deliver models with millisecond-level latency, and ensure the observability and governance necessary for AI to be production-ready. Our team is actively engaged in assessing and integrating state-of-the-art tools in the LLM and agent ecosystem, including open-source frameworks, vector databases, evaluation methodologies, and orchestration tools that empower TRM to innovate more rapidly than market demands.Your Impact:Design and implement a robust agentic framework that facilitates tool usage, context retrieval, memory integration, and strategic planning.Develop intelligent, modular agents that automate investigative workflows and enhance analyst decision-making capabilities.Expand and optimize our LLM infrastructure (e.g., OpenAI, Anthropic, on-premise models), including prompt engineering, retrieval-augmented generation, and user feedback loops.Create safe, observable, and auditable agent behaviors, ensuring reliability in sensitive operational environments.Assess performance based on metrics such as reasoning efficacy, latency, success rates, and hallucination instances, iterating based on user insights and system telemetry.Foster a culture of ownership, rapid experimentation, and ethical AI deployment.What We Seek:Proven engineering expertise with extensive experience in backend or systems development (Python preferred).Practical experience in building with LLMs, agent systems, and tooling frameworks (LangChain, semantic caches, vector databases, etc.).Strong understanding of AI principles, particularly in relation to agentic systems and LLMs.

Join Our Team at Air AppsAt Air Apps, we are on a mission to revolutionize resource management through innovative technology. Founded in 2018 in Lisbon, Portugal, we have expanded our reach with offices in both Lisbon and San Francisco, boasting over 100 million downloads globally. Our vision is to create the world’s first AI-powered Personal & Entrepreneurial Resource Planner (PRP), and we are looking for passionate individuals to help us achieve this goal.Our commitment to challenging the status quo drives us to push the boundaries of AI-driven solutions that make a real impact. Here, you will have the opportunity to be a creative force, developing products that empower individuals worldwide.Join us as we embark on this journey to redefine how people plan, work, and live.

About Brainbase LabsAt Brainbase Labs, we are pioneering the development of the first AI Workforce. We envision a future where every organization integrates AI Employees alongside their human teams, efficiently managing conversations, operations, and workflows seamlessly. Our platform is the catalyst for this transformation.In just over a year, our company has rapidly scaled from zero to over $XM in annual recurring revenue (ARR), attracting a diverse clientele from agile small and medium-sized businesses to Fortune 50 corporations. We are well-funded by premier investors and boast a globally diverse team hailing from esteemed institutions such as Harvard, Stanford, and Berkeley, united by a commitment to results, ownership, and ambition.We are in the process of expanding Brainbase Conversational, a platform that empowers teams across various sectors to build, test, deploy, monitor, and autonomously enhance conversational agents. Currently, we have achieved over 150 successful deployments across industries including automotive, hospitality, and enterprise, and we are eager to enhance our marketing efforts for this product.About The RoleWe are seeking a Founding Marketer for our Brainbase Conversational product. This is a unique opportunity to create our marketing strategy from the ground up, as no existing playbook exists.In this role, you will develop and oversee our comprehensive marketing strategy, focusing primarily on generating inbound leads. You will define our brand identity, messaging, and manage our presence across online and social media platforms.What You'll DoCraft Brainbase’s positioning, messaging, and narrative across our website, sales materials, and product offerings.Establish the initial demand generation engine through content creation, events, webinars, partnerships, and experiments that yield tangible pipeline results.Collaborate closely with the sales team to develop Ideal Customer Profiles (ICPs), refine messaging, and transform objections into valuable assets.Generate thought leadership content around AI Employees, applied AI, and the evolving landscape of work—eschewing hype for clarity and substance.Initiate and expand marketing campaigns across owned and paid channels, continually iterating based on performance signals.Develop compelling customer stories, case studies, and proof points that clearly demonstrate the product’s value proposition.Establish and uphold early brand standards regarding visual identity, voice, and tone with taste and diligence.Measure marketing performance and provide clear reports on successes, challenges, and insights.What We're Looking ForWe prioritize judgment and taste over years of experience. However, ideal candidates will likely possess:Experience in building and executing marketing strategies, preferably in a tech-focused environment.Strong understanding of digital marketing channels and lead generation tactics.Ability to analyze performance metrics and make data-driven decisions.Excellent communication and storytelling skills.

Join Scale AI's ML platform team (RLXF) as a Machine Learning Research Engineer, where you will play a pivotal role in developing our advanced distributed framework for training and inference of large language models. This platform is vital for enabling machine learning engineers, researchers, data scientists, and operators to conduct rapid and automated training, as well as evaluation of LLMs and data quality.At Scale, we occupy a unique position in the AI landscape, serving as an essential provider of training and evaluation data along with comprehensive solutions for the entire ML lifecycle. You will collaborate closely with Scale's ML teams and researchers to enhance the foundational platform that underpins our ML research and development initiatives. Your contributions will be crucial in optimizing the platform to support the next generation of LLM training, inference, and data curation.If you are passionate about driving the future of AI through groundbreaking innovations, we want to hear from you!

About Liquid AILiquid AI, a pioneering company spun out of MIT CSAIL, is at the forefront of developing general-purpose AI systems that operate efficiently across various platforms, from data center accelerators to on-device hardware. Our commitment to low latency, minimal memory usage, privacy, and reliability allows us to partner with some of the most esteemed enterprises in consumer electronics, automotive, life sciences, and financial services. As we experience rapid growth, we are seeking exceptional talent to join our innovative journey.The OpportunityJoin our cutting-edge Audio team, where we are developing advanced speech-language models capable of handling Speech-to-Text (STT), Text-to-Speech (TTS), and speech-to-speech tasks within a unified architecture. This pivotal role supports applied audio model development, directly collaborating with the technical lead to deliver production systems that operate on-device under real-time constraints. You will take ownership of key workstreams encompassing data pipelines, evaluation systems, and customer deployments. If you are eager to tackle unique technical challenges within a small, elite team where your contributions are impactful, this is the role for you.What We're Looking ForWe are seeking an individual who:Builds first, theorizes later: You prioritize shipping working systems over theoretical models; production-grade code is your default.Owns outcomes end-to-end: You take full responsibility for everything from data pipelines to customer deployments and don't shy away from challenges.Thrives under constraints: On-device, low-latency, memory-constrained environments motivate you. You view constraints as opportunities for innovative design.Ramps quickly on new territory: You are comfortable closing knowledge gaps swiftly and actively seek feedback to drive results.The WorkDevelop and scale data pipelines for audio model training, including preprocessing, augmentation, and quality filtering at scale.Design, implement, and maintain evaluation systems that assess multimodal performance across both internal and public benchmarks.Fine-tune and adapt audio models to cater to customer-specific use cases, taking charge from requirement gathering through to deployment.Contribute production code to the core audio repository while collaborating closely with infrastructure and research teams.Facilitate experimentation under real hardware constraints, transitioning smoothly between customer-focused projects and core development initiatives.

About Pax HistoriaPax Historia is pioneering a new genre of gameplay by leveraging cutting-edge generative AI technologies. Our innovative platform combines the strategic depth of grand strategy games with the limitless creativity of a sandbox environment, driven by a vibrant community that actively creates and modifies scenarios.Our user base generates hundreds of scenarios daily and engages in millions of game rounds each week, exhibiting rapid growth. We are proud to be supported by esteemed investors such as Y Combinator, Pace Capital, and Z Fellows. Your contributions will have an immediate impact on a product enjoyed by hundreds of thousands of players.Position OverviewWe are seeking a founding-level ML Systems Engineer to join our team in-person full-time in San Francisco (Dogpatch). You will have the opportunity to work closely with our cofounders to shape the future of our technology.Current Challenges:Closed-source models yield satisfactory game performance but come with high costs.Open-source models are more budget-friendly yet often underperform in our environment.Prompts and harnesses exhibit minimal variance across models.We have a functional internal evaluation system with significant opportunities for enhancement.Your Responsibilities:Establish and manage the necessary infrastructure for customizing harnesses and prompts tailored to individual AI models to optimize their performance.Develop domain-specific models aimed at narrowing or completely bridging the gap in performance between open and closed models.Optimize caching strategies to decrease expenses associated with closed-source models.Enhance the performance of closed-source models by training specialized endpoints.Assess and advance the effectiveness of embedding and reranking mechanisms in our applications.Facilitate the creation of new user experiences based on emerging world models.In Summary: Your work will directly enhance the affordability and enjoyment of the game.

Join our innovative team at Lila Sciences as an AI Lab Research Engineer. In this role, you will contribute to cutting-edge AI research and development, focusing on enhancing the capabilities of our laboratory systems. Your expertise will help drive forward our mission to revolutionize scientific research through artificial intelligence.

Gimlet Labs is pioneering the future of artificial intelligence by developing a groundbreaking platform for next-generation AI applications. As the demand for generative AI workloads surges, we are addressing the critical challenge of inference efficiency, which is essential for optimal performance. Our innovative approach to AI inference combines state-of-the-art research with a fully integrated hardware-software stack, pushing the boundaries of performance, efficiency, and model quality.We pride ourselves on providing a seamless experience for developers, empowering them to deploy, manage, and monitor AI workloads from frameworks like PyTorch and LangChain at production scale in just seconds. Our founding team boasts extensive experience across AI, distributed systems, and hardware, with a track record of successful ventures.We are excited to welcome our first marketing hire who will play a crucial role in establishing Gimlet's marketing function from the ground up. This position is tailored for a passionate marketer who enjoys crafting engaging content, connecting with developer communities, and running comprehensive marketing campaigns from start to finish.