Founding Audio AI Research Engineer

Join Our Innovative Team at David AIDavid AI is pioneering the audio data research landscape. We adopt a rigorous R&D methodology for developing datasets that parallels the standards upheld by leading AI laboratories. Our vision is to seamlessly integrate AI into everyday experiences, with audio serving as the perfect conduit. The evolution of audio AI is rapidly unfolding, yet the availability of high-quality training data remains a critical challenge. This is where David AI steps in.Founded in 2024 by a talented group of former engineers and operators from Scale AI, we have quickly become a trusted partner to numerous FAANG companies and AI research labs. Recently, we secured $50 million in a Series B funding round with notable investors, including Meritech, NVIDIA, and Alt Capital.Our culture is built on sharp intellect, humility, ambition, and a close-knit community. We invite exceptional minds in research, engineering, product development, and operations to join us as we advance the field of audio AI.Research Team OverviewAt David AI, we are convinced that superior model capabilities stem from high-quality, differentiated data. Our research team is dedicated to conducting ambitious, long-term studies into audio technology while collaborating with both internal and external partners to implement cutting-edge research insights into practical applications.Your Role as a Founding Audio AI Research EngineerIn this position, you will establish the research framework that influences how premier AI labs develop their audio models. You will have access to a top-tier team of human AI trainers, robust computing resources, and the autonomy to shape your research agenda.Key ResponsibilitiesCreate and implement comprehensive evaluation frameworks for assessing audio AI capabilities in areas such as speech, emotion detection, conversational dynamics, and acoustic patterns.Investigate and prototype innovative methodologies for audio quality assessment, automated labeling, and optimizing data collection processes.Design focused data collection pipelines aimed at capturing novel, high-value audio capabilities.Develop automated systems for ongoing classifier enhancement and prompt engineering evaluation.Assess cutting-edge models and formulate actionable research strategies.Publish your findings in prestigious conferences.

Zyphra is an innovative artificial intelligence company located in the heart of San Francisco, California.The Opportunity:Join our dynamic team as a Research Engineer - Audio & Speech Models, where you will play a pivotal role in advancing Zyphra’s Audio Team. You will be instrumental in developing cutting-edge open-source text-to-speech and audio models. Your contributions will span the full spectrum of the model training process, from data collection and processing to the design of innovative architectures and training approaches.Your Responsibilities:Conduct large-scale audio training operationsOptimize the performance of our training infrastructureCollect, process, and evaluate audio datasetsImplement architectural and methodological improvements through rigorous testingWhat We Seek:A strong research mindset with the ability to navigate projects from ideation to implementation and documentation.Proficiency in rapid prototyping and implementation, allowing for swift experimentation.Effective collaboration skills in a fast-paced research environment.A quick learner who is eager to embrace and implement new concepts.Excellent communication abilities, enabling you to contribute to both research and engineering tasks at scale.Preferred Qualifications:Expertise in training audio models, such as text-to-speech, ASR, speech-to-speech, or emotion recognition.Experience with training audio autoencoders.Solid understanding of signal processing, particularly in audio.Familiarity with diffusion models, consistency models, or GANs.Experience with large-scale (multi-node) GPU training environments.Strong understanding of experimental methodologies for conducting rigorous tests and ablations.Interest in large-scale, parallel data processing pipelines.Competence in PyTorch and Python programming.Experience contributing to large, established codebases with rapid adaptation.

At Thinking Machines Lab, our mission is to enhance humanity's potential through the advancement of collaborative general intelligence. We envision a future where everyone can access the knowledge and tools necessary to leverage AI for their individual needs and objectives.As a team of scientists, engineers, and innovators, we have developed some of the most widely utilized AI products, such as ChatGPT and Character.ai, along with open-weight models like Mistral, and popular open-source projects including PyTorch, OpenAI Gym, Fairseq, and Segment Anything.Role OverviewAt Thinking Machines, we adopt a multimodal-first approach, where multimodality is integral to our scientific goals and infrastructure. We are seeking skilled researchers to push the boundaries of audio capabilities. In this role, you will delve into how audio models can facilitate more natural and efficient communication and collaboration by preserving information and accurately capturing user intent.This position requires strong collaboration across pre-training, post-training, and product development with top-tier researchers, infrastructure engineers, and designers. Here, you will have the chance to influence the foundational capabilities of AI systems that will be utilized by millions globally.This role marries fundamental research with practical engineering, as we do not separate these functions internally. You will be expected to write high-performance code as well as engage with technical reports. It is an ideal position for someone who enjoys both extensive theoretical research and hands-on experimentation while laying the groundwork for how AI learns.Note: This is an evergreen role that remains open continuously to gauge interest in this research area. We receive numerous applications, and there may not always be an immediate match for your skills and experience. Nevertheless, we encourage you to apply, as we routinely review applications and reach out as new opportunities arise. You are welcome to reapply if you gain additional experience, but please avoid applying more frequently than every six months. Occasionally, we also post specific roles for distinct project or team needs, in which case you are welcome to apply directly alongside an evergreen submission.

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.

Join Canva as a Staff Research Scientist specializing in Video & Audio Generative AI. In this pivotal role, you will leverage your expertise in AI to develop innovative solutions that enhance our platform's multimedia capabilities. Collaborate with cross-functional teams to push the boundaries of AI technology, driving impactful projects that redefine user experiences.

Join David AI as a Product ManagerDavid AI is pioneering the audio data research landscape, harnessing an R&D methodology to develop high-quality datasets that support AI models. Our vision is to seamlessly integrate AI into everyday experiences, with audio serving as the perfect entry point. As the demand for advanced audio AI solutions grows, the necessity for superior training data becomes paramount, and David AI is at the forefront of this evolution.Founded in 2024 by a talented team of former engineers from Scale AI, we’ve quickly established ourselves as a trusted partner for leading FAANG companies and AI labs. Our recent $50M Series B funding round, led by top-tier investors including Meritech and NVIDIA, is a testament to our trajectory and potential.We pride ourselves on our team’s intelligence, humility, and ambition. If you are passionate about research, engineering, product development, or operations, we invite you to contribute to our mission of advancing audio AI.The Product TeamOur Product team operates at the intersection of research, engineering, and operations, crafting audio data products that empower cutting-edge machine learning models. We translate groundbreaking research into scalable and thoughtful data products that prioritize quality, coverage, and clarity for model creators.Your RoleAs a Product Manager on our Product team, you will take charge of the strategy and execution of key components within our audio data portfolio. Collaborating closely with the Research, ML, Engineering, and Operations teams, you will convert model requirements into actionable data roadmaps, quality standards, and deliverables ready for clients.Key ResponsibilitiesSpecialize in areas such as data roadmap expansion, quality metrics, and evaluation based on your interests and background.Lead product strategy and development for audio data offerings, guiding them from research to full-scale production.Convert research insights into specific requirements for data collection, quality assurance, and documentation.Work in partnership with Research, ML, Engineering, and Operations teams to operationalize new datasets and capabilities.Establish metrics and success criteria to prioritize initiatives and evaluate impact across quality, coverage, cost, and speed.

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.

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.

Join Us at Amplifier Health!We are pioneering healthcare innovations with the world's first Large Acoustic Model (LAM), a groundbreaking foundation model that utilizes human voice to identify health conditions. This is where science fiction meets reality, and we have secured substantial funding from leading investors to establish a transformative new category in healthcare.We are in search of a passionate AI researcher who is ready to break free from the traditional "publish or perish" mindset and focus on creating impactful intelligence that truly works in real-world applications.The Reality of Our WorkWe are entering an exhilarating phase of rapid growth. Our commitment to pushing the boundaries of technology is matched only by our dedication to saving lives at scale.Our team collaborates in person in San Francisco, believing that the most challenging problems are best tackled together at a whiteboard rather than through virtual meetings.We operate at a fast pace, quickly transitioning from hypothesis to code, training, and validation with immediate feedback.We enjoy our work and thrive as a close-knit team on an exciting journey, driven by our passion for what we do.Your MissionAs part of our elite AI Research team, you will elevate the state-of-the-art in acoustic modeling. Your role will involve designing innovative architectures to extract clinical-grade biomarkers from raw audio data, not just fine-tuning existing models.The Challenges Ahead:Novel Architectures: You will explore how Transformer architectures can be adapted to process complex acoustic signals and long-range dependencies.Biomarker Discovery: You will conduct experiments to identify specific acoustic features (such as jitter, shimmer, and respiratory rate) that correlate with health conditions, often uncovering new signals that have yet to be recognized by medical science.Data Efficiency: You will contribute to building a foundation model, utilizing self-supervised learning techniques to harness vast amounts of unlabeled audio data.

About UsTavus is an innovative research lab at the forefront of human computing technology. Our mission is to create AI Humans—advanced interfaces that bridge the gap between individuals and machines, eliminating the friction found in current systems. Our real-time human simulation models empower machines to see, hear, respond, and appear realistic, facilitating genuine, face-to-face conversations. With AI Humans, we blend the emotional intelligence inherent in humans with the extensive reach and reliability of machines, enabling them to serve as capable and trusted agents available 24/7, capable of communicating in any language.Envision a therapist accessible to everyone, a personal trainer that tailors sessions to your schedule, or a fleet of medical assistants dedicated to providing personalized attention to every patient. Tavus enables individuals, enterprises, and developers to create AI Humans that connect, empathize, and act with understanding on a large scale.Backed by prestigious investors like Sequoia Capital, Y Combinator, and Scale Venture Partners, we are a Series A company ready to shape the future of human-machine interaction.Join us in transforming a future where humans and machines genuinely comprehend one another.The RoleWe are seeking a passionate AI Researcher to join our core AI team and advance the science of audio-visual avatar generation. If you thrive in dynamic startup environments, enjoy experimenting with generative models, and are excited to see your research translated into production, you will find a welcoming home here.Your Mission Conduct research and develop cutting-edge audio-visual generation models for conversational agents (e.g., Neural Avatars, Talking Heads).Focus on models that intricately align with conversation flows, ensuring seamless integration of verbal and non-verbal cues.Experiment with diffusion models (DDPMs, LDMs, etc.), long-video generation, and audio synthesis.Collaborate closely with the Applied ML team to transition your research into practical applications.Stay updated on the latest breakthroughs in multimodal generation and contribute to the evolution of this field.You Will Excel If You Have:A PhD (or nearing completion) in a relevant discipline, or equivalent hands-on research experience.Proficiency in applying image/video generation techniques and a solid understanding of machine learning principles.

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.

Join Pensive as a Founding Engineer (AI/GTM)At Pensive, our mission is to harness the power of AI to revolutionize education and streamline business operations. Visit our Notion page to explore our vision, meet our founders, and understand our culture.Your Role and ContributionsAs a Founding Engineer specializing in AI and Go-To-Market (GTM) strategies, you will play a pivotal role in shaping our AI-driven solutions. Your innovative approach will be vital in developing automated systems that enhance our grading and tutoring platform, helping educators and students achieve more.You will be responsible for:Developing traditional AI engineering solutions, creating AI pipelines that optimize our educational platform for instructors and students alike.Implementing GTM engineering strategies to enhance customer management, business growth, and operational efficiency.Automating various business processes, from data management to customer onboarding, ensuring seamless operations.Example tasks include:Monitoring and enhancing the AI performance of our grading system.Creating a system for automated course categorization that aligns with our offerings.What We SeekWe are in search of dynamic individuals who are adept at leveraging AI to tackle challenges and drive solutions. Essential qualifications include:Exceptional problem-solving abilities and creativity.A strong understanding of AI-generated code, particularly in backend and AI-related domains.A quick learner who can thrive in a fast-paced environment.Preferred QualificationsExperience in prompt engineering and AI pipeline development.Hands-on experience in building applications from the ground up.Capability to write or comprehend frontend code.Our Technology StackFamiliarity with the following technologies is not mandatory for this role:Backend: Python, FastAPI, PostgresFrontend: TypeScript, React, TailwindCSS, Tanstack RouterInfrastructure: GCP, Cloud Run, FirebaseMobile App Development: CapacitorInterview ProcessWe look forward to welcoming you to our team!

bland is looking for a Machine Learning Researcher with a focus on audio. This position is based in San Francisco and centers on advancing how machines process and understand sound. The team works on pushing the boundaries of audio technology for a range of platforms. Responsibilities Research and develop new machine learning techniques for audio applications Contribute to projects that improve audio processing and analysis Collaborate with colleagues to bring research ideas into real-world audio products Location This role requires working onsite in San Francisco.

About Retell AI Retell AI develops advanced voice AI technology for call centers, using first-principles approaches to create intelligent voice agents. These agents help businesses manage sales, support, and logistics communications while reducing reliance on large human teams. The company has reached $36M ARR in just 18 months, backed by Y Combinator and Alt Capital. With a team of 20, Retell AI is building a comprehensive customer experience platform, aiming for AI-powered contact centers by 2026. The vision: intelligent agents that execute, monitor, and improve customer interactions with minimal human oversight. Named a top 50 AI app by a16z: https://tinyurl.com/5853dt2x Ranked #4 on Brex's Fast-Growing Software Vendors of 2025: https://www.brex.com/journal/brex-benchmark-december-2025 Featured among top startups: https://leanaileaderboard.com/ Role Overview: Research Scientist - Voice AI Innovation This role centers on advancing machine learning for human-like voice agents in real-world settings. The Research Scientist will explore new methods in large language models (LLMs) and audio models, design evaluation techniques, and prototype systems that improve reasoning, reduce latency, and enhance conversational quality. The work involves open-ended ML challenges, rapid experimentation, and direct influence on the performance and cognitive abilities of voice AI systems at scale. Location San Francisco Bay Area

Founding Research EngineerLocation: San Francisco (On-site)Compensation: $200,000 – $250,000 + variable equity based on cash compensationAbout UsLotus Health is an innovative primary care application that seamlessly integrates medical records, artificial intelligence, and real healthcare professionals to deliver personalized, no-cost healthcare and prescription services. Our team is composed of seasoned entrepreneurs and engineers who have successfully developed and scaled consumer applications to millions of users, generating over $100 million in annual revenue. We are proudly supported by notable investors like Kleiner Perkins and esteemed clinicians from Harvard and Stanford.Role OverviewWe are seeking a talented Founding Research Engineer to conceptualize, prototype, and implement the fundamental reasoning and agentic systems that drive Lotus. You will transform complex health data into precise, well-cited, and actionable insights for both patients and healthcare providers. This position uniquely combines applied research with product engineering, encompassing dataset management, model training and assessment, retrieval and tool utilization, safety, alignment, and the deployment of innovative breakthroughs. You will collaborate closely with clinicians and the founding team, ensuring your work has a direct impact on patient care.ResponsibilitiesResearch and ModelingDevelop and refine agentic workflows that leverage retrieval, function invocation, and strategic planning to effectively address health inquiries, complete with citations and awareness of uncertainty.Optimize and refine models focused on summarization, extraction, classification, and dialogue, grounded in medical datasets.Establish strategies for abstention, routing, and fallback that prioritize safety and accuracy.Datasets and LabelingCurate high-quality datasets from electronic health records, claims, laboratories, devices, and chat interactions, ensuring thorough de-identification.Create synthetic data and clinician-in-the-loop labeling frameworks that accurately represent real-world clinical applications.Evaluation and SafetyTake ownership of the evaluation stack regarding medical accuracy, hallucination management, bias assessment, safety, latency, and cost efficiency.Develop automated red teaming and regression testing suites aligned with clinical guidelines and source citations.

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.

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 future of enterprise AI infrastructure, focusing on agents, retrieval-augmented generation (RAG), knowledge graphs, and multi-tenant governance.As an ML/AI Research Engineer, you will spearhead the design, training, evaluation, and optimization of agent-native AI models. Your work will integrate LLMs, vector search, graph reasoning, and reinforcement learning, establishing the intelligence layer for our enterprise data fabric.This role goes beyond prompt engineering; it encompasses the entire ML lifecycle—from data curation and fine-tuning to thorough evaluation, interpretability, and deployment, all while considering cost-effectiveness, alignment, and agent coordination.Core ResponsibilitiesFine-tune and assess open-source LLMs (e.g., LLaMA 3, Mistral, Falcon, Mixtral) for enterprise applications, leveraging both structured and unstructured data.Construct and enhance RAG pipelines utilizing LangChain, LangGraph, LlamaIndex, or Dust, integrating with our vector databases and internal knowledge graphs.Train agent architectures (ReAct, AutoGPT, BabyAGI, OpenAgents) using enterprise task datasets.Develop embedding-based memory and retrieval chains employing token-efficient chunking strategies.Create reinforcement learning pipelines to enhance agent behaviors (e.g., RLHF, DPO, PPO).Establish scalable evaluation harnesses for LLM and agent performance, including synthetic evaluations, trace capture, and explainability tools.Contribute to model observability, drift detection, error classification, and alignment efforts.Optimize inference latency and GPU resource utilization across both cloud and on-premises environments.Desired ExperienceModel Training:Deep understanding of machine learning principles and hands-on experience with model training.

About David AIDavid AI is pioneering the audio data research landscape, applying a rigorous R&D approach to dataset development akin to the methodologies used in AI labs for model creation. Our goal is to integrate AI seamlessly into real-world applications, with audio serving as the perfect entry point due to its inherent versatility and human connection. As the audio AI field progresses, the demand for high-quality training data becomes critical, and that's where David AI excels.Founded in 2024 by a team of experienced engineers and operators from Scale AI, David AI has quickly gained traction, serving prominent clients among FAANG companies and AI research labs. Recently, we secured a $50M Series B funding round from esteemed investors including Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, and First Round Capital.Our team embodies intelligence, humility, ambition, and a close-knit ethos. We are on the lookout for exceptional talent in research, engineering, product, and operations to join us in advancing the frontiers of audio AI.About Our Engineering TeamAt David AI, our engineering team is responsible for constructing the pipelines, platforms, and models that convert raw audio into valuable data for top AI labs and enterprises. We pride ourselves on our collaborative environment, comprising product engineers, infrastructure specialists, and machine learning experts dedicated to leading the charge in audio data research.We operate at a fast pace, taking ownership of our projects from conception through to production. Our team develops real-time processing pipelines capable of managing terabytes of audio data daily while deploying innovative generative audio models.About This RoleAs a Product Engineer at David AI, you will design and implement state-of-the-art tools that enable our users to leverage audio data effectively for training their AI models. You will collaborate closely with researchers to continuously refine our data collection methodologies.Your ResponsibilitiesDeliver full-stack features that will be utilized by thousands of users on a daily basis.Develop scalable systems that create essential data processing pipelines, extracting actionable insights from terabytes of audio data each day.Construct, deploy, and assess LLM and DSP-based solutions to enhance our clients' comprehension of intricate features within our datasets.Rapidly iterate on research hypotheses by collaborating with researchers and the operations team to deploy enhancements efficiently.

Join Shiplight AI as a Founding Engineer, AIAre you ready to be at the forefront of the AI revolution and make a significant impact?Do you believe in enhancing productivity exponentially through innovative solutions?At Shiplight AI, we are on a mission to redefine enterprise-scale automation through intelligent agents. We envision a future where organizations leverage AI systems capable of understanding context, taking meaningful actions, and seamlessly collaborating with humans — transforming workplace dynamics.Our initial goal is to revolutionize software quality assurance. We are developing cutting-edge agentic QA systems that integrate deeply within the software development lifecycle, empowering every product manager, developer, and tester with their own AI QA engineer for real-time validation of their work.You will be part of a small, dedicated founding team led by industry experts, focusing on the intersection of AI agents, systems engineering, and enhancing real-world developer productivity.

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.