AI Startup Jobs

SecureBio is seeking a Senior Research Scientist to join their AI Biosecurity Assessments team. In this role, you will evaluate frontier AI models for dual-use biological risks before their public release. This involves running technical assessment pipelines, analyzing model behavior, and producing reports that inform relevant audiences about identified risks. Your work will contribute to setting industry safety standards and influencing policy bodies like the NIST US AI Safety Consortium and the European AI Office. You will collaborate with AI firms, internal research teams, and policy makers to ensure the safe development and deployment of advanced AI technologies.

$235k - $300k

About HUD HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs. About the role We’re looking for a Research Engineer for our Robotics team to develop the datasets and evals that make robotics data useful for training and evaluating embodied AI systems. You’ll translate open-ended research needs into data specifications, build methods to validate data, and run experiments to understand which data and structures improve model performance. Responsibilities - Research the data needs of robot learning and physical AI systems, and turn them into concrete dataset and evaluation specifications - Define data schemas, annotations, ground truth, and quality standards across robotics data types - Design collection and review protocols that external data providers can execute reliably - Build tools and validation workflows to audit datasets, identify quality issues, and give providers actionable feedback - Run experiments and analyze model behavior to understand how data quality, coverage, and structure affect performance - Work with HUD’s research and engineering teams, and when needed with data vendors and buyers, to improve robotics data offerings Experience You may be a good fit if you have: - Experience in robotics, robot learning, embodied AI, or closely related multimodal research - Proficiency in Python and experience building data processing, analysis, or evaluation tools - Experience turning research questions into dataset specifications, experiments, and measurable quality criteria - Strong understanding of what makes robotics data useful for training or evaluation—and where it can be misleading - Attention to detail and the ability to spot subtle errors, coverage gaps, and failure modes in complex data - Experience building research tools or pipelines without a fully prescribed roadmap Strong candidates may also have: - Worked with robot trajectories, demonstrations, video, sensor data, simulation, or other multimodal robotics datasets - Experience with imitation learning, reinforcement learning, or vision-language-action models - Worked in unstructured problem spaces and take ownership from early research through production deployment - Early-stage startup experience and strong communication skills for collaboration across teams and time zones We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria. Team & company details - Team Size: ~25 people currently, mostly full-time in-person, but some remote. - Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. - Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand. Logistics - Employment: Full-time. - Location: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones. - Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore. - Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial. What we offer - Competitive compensation - 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees) - Lunch and dinner for in-office employees - Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays - Other perks including an Equinox membership, 401k, and commuter benefits (US employees) and a health/wellness stipend (Singapore employees) - Unlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is. - Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place - Annual travel budget to visit either office Compensation Actual offers are adjusted for experience and location, but our base salary bands are - San Francisco (and other major US cities): $135,000 - $230,000 - Singapore: $100,000 - $175,000 - Rest of world: $100,000 - $175,000 Due to high volume, we may not actively respond to every application, but feel free to contact us at [email protected] or elsewhere if we missed your application!

$100k - $230k

Handshake is seeking a Member of Technical Staff to join their AI Engineering team. This role is crucial for building and improving the data systems that power frontier model training. You will be responsible for enhancing how Handshake generates, processes, and prepares complex and sensitive data, including creating high-quality synthetic data and anonymizing acquired data while preserving its value. You will collaborate with researchers, domain experts, legal teams, and customers to transform data-related challenges into experiments, pipelines, and products, influencing the company's technical direction and culture.

$200k - $350k

Mirage is seeking an ML Engineer to push the boundaries of large language models for multimodal creative tasks. You'll develop new approaches for building and extending agentic systems that understand and operate over complex, real-world data, particularly video. This role focuses on advancing agent capabilities, improving reasoning and control, and enabling new forms of interaction between language models and time-based media.

$175k - $300k

Haven Safety AI is building an enterprise learning intelligence layer for safety, designed to help high-risk organizations learn faster from incidents and prevent future occurrences. The platform integrates with existing EHS systems to enhance incident investigation, assessment, and learning processes. It leverages current incident evidence, company knowledge, historical cases, and an industry knowledge graph, with specialized AI agents analyzing various data points to produce traceable assessments. This role is a build-and-operate position focused on the AI and LLM engineering layer, connecting the evidence base and knowledge graph to the product experiences used by investigators and safety leaders. The work is technically demanding and operationally critical, serving enterprise customers in regulated, safety-critical industries where precision, traceability, evaluation, and human oversight are paramount.

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Mirage is seeking an ML Engineer to build and scale the systems powering their video generation models. This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation. You will work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production.

$175k - $300k

Haven Safety AI is building an enterprise learning intelligence layer for safety, helping high-risk organizations learn faster from incidents to prevent future occurrences. The platform integrates with existing EHS systems to enhance how incidents are investigated, assessed, and learned from. It combines incident evidence, company knowledge, historical cases, and an industry knowledge graph, with specialized AI agents analyzing various factors to produce traceable assessments. This role focuses on the AI and LLM engineering layer, connecting the evidence base and knowledge graph to the product experiences used by investigators and safety leaders. It's a build-and-operate role requiring technical expertise and operational responsibility in a safety-critical, multi-tenant enterprise environment.

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PostEra

PostEra is seeking a Machine Learning Researcher to spearhead the development of an agentic research vertical. This role involves leveraging agentic systems to automate the creation of mechanistic models for biochemical and physiological processes, and to analyze biological data for target validation. You will collaborate closely with chemists and biologists to guide drug discovery decisions using these models. A key focus will be on developing machine learning methods capable of rapid adaptation to new drug discovery challenges with limited labeled data, particularly in molecular and tabular in-context learning and building foundation models from proprietary multimodal data. You will be responsible for the entire research loop, from defining tasks and constructing datasets to training and scaling models, performing rigorous ablations, and translating successful methods into practical capabilities for PostEra's scientists. While prior drug discovery experience is not mandatory, a strong motivation to learn the domain and collaborate with interdisciplinary scientists is essential.

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HeyGen is building AI applications including Avatar IV, Photo Avatar, Interactive Avatar, and Video Translation. We are looking for a Software Engineer focused on GPU performance to make the systems behind these experiences faster and more efficient. You will work across model execution and inference infrastructure, using profiling and measurement to improve latency, throughput, and GPU cost. This role is a fit for an engineer who enjoys understanding how software uses the hardware beneath it.

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Tavus

Tavus is building the human layer of AI, aiming to make human-AI interaction as natural as face-to-face communication. We pioneer research in multimodal AI for modeling human communication (language, audio, video) and generating audio-visual avatar behavior, powering applications from text-to-video avatars to real-time conversational video. We are a Series B company backed by top investors, seeking individuals who thrive in startup environments, can prioritize independently, and are willing to take calculated risks to help pave the path forward.

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Salient

Salient is seeking a Telephony Infrastructure Engineer to take ownership of the voice platform that powers our AI agents. This role involves managing the SIP edge, Asterisk, voice audio and dialing layers, and call servers. You will collaborate with AI agent engineers, telephony specialists, customer success teams, and carriers to ensure the platform's reliability, safety, and scalability for future growth. This is a hands-on position where you will complete ongoing projects, enhance platform stability, and prepare it to handle significantly increased call volumes. Additionally, you will design and implement customer telephony integrations, working towards making these processes more self-serve.

$200k - $300k

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI trainers. We are a growing team of researchers, engineers, and operators backed by significant VC funding. We are seeking a Research Manager to lead research focused on enhancing HUD's agent training data and evaluations for frontier models. This role involves guiding research engineers through complex projects, translating findings into scalable methods, and staying technically engaged while ensuring rigorous experimentation and impactful results. The ideal candidate will possess a deep understanding of model training dynamics, including how signals, data, and evaluation design influence outcomes.

$120k - $295k

Chai Discovery

Chai Discovery is building the computer-aided design suite for molecules, with major pharmaceutical companies already using their platform to accelerate drug discovery. They are at the forefront of reinventing life sciences through AI, developing frontier models that understand biochemical structure and interaction. This role is an opportunity to push the boundaries of AI drug design alongside a skilled and dedicated team.

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Eventual is building data curation for Physical AI, processing petabyte-scale video and sensor data to extract signals about how hands and objects interact, temporal events, and clip reliability for training frontier models. We are a small, well-backed team from leading tech companies, aiming to revolutionize how Physical AI models are trained by providing reliable, curated datasets derived from vast amounts of video footage. This role is based in our SF Mission District office, with a 4-day work week. As Technical Lead, Multimodal Research, you will drive the technical vision for Eventual's understanding of video data. You will own the strategy for selecting, prototyping, and deploying models and representations at scale, ensuring they meet rigorous evaluation standards and cost-efficiency targets. This is a senior individual contributor role focused on setting research direction and making key architectural decisions, while remaining hands-on with research and experimentation.

$150k - $300k

LangChain is seeking an experienced frontend engineer to develop and enhance new features on LangSmith, their enterprise platform for LLM application observability, testing, and debugging. This role is crucial for building the foundation of agent engineering in the real world, helping developers move from prototypes to production-ready AI agents. The LangSmith team owns and builds the core platform for observability, evaluation, and production reliability of AI systems, from tracing and annotation to run rules and evaluations.

$170k - $235k

Cartesia

Cartesia is pioneering AI architectures that learn and interact with the world like humans. We are seeking a Research Engineer, Data Infrastructure to build the datasets and systems essential for pretraining our foundational models. This role involves developing performant, scalable infrastructure for acquiring, processing, and curating massive datasets, and collaborating closely with research teams to optimize data composition. Your contributions will directly influence the capabilities and quality of our cutting-edge models.

$200k - $350k

Typeface

We help the world's biggest brands move from brief to fully personalized campaigns in days, not months. Founded by Abhay Parasnis and backed by Microsoft, GV, Salesforce, Lightspeed, Madrona and Menlo, we’re building category-defining technology at the intersection of creativity and AI with real impact. Join us to help shape the future of enterprise marketing.

$188k - $200k

Typeface

We help the world’s biggest brands move from brief to fully personalized campaigns — in days, not months. Founded by Abhay Parasnis and backed by Microsoft, GV, Salesforce, Lightspeed, Madrona and Menlo, we’re building category-defining technology at the intersection of creativity and AI with real impact. Join us to help shape the future of enterprise marketing. We are looking for strong full-stack engineers across multiple levels to join our team and help us build innovative and elegant web applications and cloud services that deliver the power of Generative AI to our customers.

$210k - $240k

Tenstorrent is at the forefront of AI technology, aiming to revolutionize performance, usability, and cost-efficiency. As AI reshapes computing, our solutions must integrate software models, compilers, platforms, networking, and semiconductors. We have developed a high-performance RISC-V CPU and are seeking passionate individuals to build the ultimate AI platform. Our Tensix Team is architecting the future of AI compute with scalable RISC-V processors, focusing on reimagining RISC-V core frontends for enhanced programmability, efficiency, and developer experience. This is a unique opportunity to influence the CPU architecture at the core of our AI platform and lead a critical technical initiative.

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Tenstorrent is seeking a Physical Design Methodology Engineer to develop, deploy, and own the RTL-to-GDSII methodology for their AI hardware IP team. This role is crucial for ensuring that new blocks, nodes, or customer variants can start from a working flow, rather than a cold start. The ideal candidate will be automation-minded, focused on removing manual steps and making PPA exploration repeatable, and will leverage AI, including LLMs and ML-driven optimization, in their flow development. This is a hybrid role based in Toronto, Austin, or Belgrade, and the company welcomes candidates at various experience levels.

$100k - $500k

Tenstorrent is seeking a RISC-V AI / HPC & Agentic Software Engineering Lead to work at the hardware-software boundary, enabling AI, HPC, and agentic AI software stacks on Tenstorrent’s RISC-V processors. This role involves integrating and optimizing Tenstorrent’s LLK (Low-Level Kernel) infrastructure for CPU execution and leading the bring-up of a RISC-V-native agentic AI software stack. You will collaborate closely with CPU architects, microarchitecture teams, compiler engineers, and AI kernel developers to ensure tight alignment between software capabilities and RISC-V architectural features. This is a remote position based out of North America.

$100k - $500k

Tenstorrent is seeking a Physical Design Engineer to lead cross-functional efforts in solving complex physical design challenges and developing end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. We welcome candidates at various experience levels for this role, and offers will align with the assessed level.

$100k - $500k

Tenstorrent is a leader in AI technology, developing next-generation AI compute solutions. The Kernel Development and Optimization team is crucial in unlocking the full potential of their hardware for ML and HPC workloads by creating performance-critical kernels. This role involves designing, implementing, and optimizing GPU-style kernels, contributing to host-side orchestration, and ensuring kernel correctness and performance through rigorous testing and collaboration with various engineering teams. You will gain deep insights into AI hardware, learn to optimize kernels outside traditional CUDA ecosystems, and explore AI-assisted workflows for kernel development.

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This role sits at the intersection of technical expertise and customer engagement, focused on helping customers and internal teams bring up and optimize AI models on Tenstorrent platforms. As a Software Engineer on the AI Models / System Bring-Up team, you will be responsible for porting, validating, and optimizing AI models on Tenstorrent platforms. Working across models, runtime software, and hardware, you will help connect new models, models not yet running on Tenstorrent hardware, and research-stage workloads to stable, high-performance systems.

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