Job Description
Machine Learning Engineer / Researcher — Hestus David Joseph & Company San Mateo, CA Job Details Full-time $110,000 - $175,000 a year 17 hours ago Benefits Health insurance Dental insurance Vision insurance Qualifications AI models Technical documentation Research Production systems Machine intelligence Model deployment Requirements analysis Developing large-scale AI models Developing data pipelines APIs Model training System deployment Business requirements MLOps Full Job Description Machine Learning Engineer / Researcher — Hestus (YC)
Location:
San Mateo, CA (Onsite preferred — open to Bay Area candidates willing to commute) Compensation:
$110,000 - $175,000 base + meaningful equity Visa Sponsorship:
None available — US work authorization required Experience Level:
4+ years (or equivalent research-based Master's / PhD) Employment Type:
Full-Time About Hestus Hestus is building AI-powered CAD to fundamentally change how hardware is designed and manufactured. Founded by repeat deep-tech entrepreneurs with experience from top YC companies and frontier robotics, Hestus is turning CAD into an intelligent collaborator that understands design intent and autocompletes the work — letting hardware teams move from weeks of repetitive clicking to minutes of high-leverage engineering. YC-backed, 5-10 person team based in San Mateo. About the Role This is the first senior ML and research hire at Hestus. You will own the full lifecycle of ML systems powering the AI-driven CAD product — moving between deep research and hands-on engineering, scoping problems with the founders, designing and training novel models, and shipping them into robust production code. Over time you will have the opportunity to define the roadmap for CAD-focused ML research, mentor future hires, and grow into a Staff/Principal IC or early engineering leader. What You'll Own Design, train, and iterate on custom deep learning models that understand CAD workflows and predict high-quality next-step suggestions Build and maintain robust Python training and evaluation pipelines — data preprocessing, experimentation, and offline/online metrics Architect model serving and backend components so features are fast, reliable, and easy to integrate into CAD environments Work closely with the founder and early customers (mechanical and hardware engineers) to understand real-world workflows and translate them into ML formulations Own the full lifecycle of ML features — from research and prototyping through productionization, deployment, and monitoring Collaborate with the broader engineering team on core product and infrastructure work — backend, APIs, data models, performance Establish best practices for experimentation, logging, and model comparison Stay current on relevant ML research (sequence models, geometric deep learning, representation learning) and apply pragmatically Requirements 4+ years of hands-on ML experience, or equivalent research-based Master's or PhD Proven track record of training and improving deep models — not just calling hosted APIs Expert with PyTorch (preferred), TensorFlow, or JAX — comfortable implementing and modifying custom architectures, loss functions, and training loops Strong production-ready Python — clean, well-structured, with tests, documentation, and thoughtful abstractions End-to-end ownership experience — data to deployment, training pipelines, hyperparameter tuning, shipping models into real products Ability to work closely with founders and translate open-ended product requirements into concrete ML formulations Able to commute to San Mateo for onsite or hybrid work US work authorization required — no sponsorship available Nice to Have Experience with geometry, graphics, CAD, 3D representations, or robotics Familiarity with cloud ML platforms (AWS/GCP) and backend frameworks (FastAPI, Flask, Django) Published research or meaningful open-source contributions demonstrating novel technical work Benefits Competitive salary and meaningful equity Comprehensive medical, dental, and vision coverage Catered team lunch in the San Mateo office Unlimited / flexible time off High-ownership role on a small, senior founding team Interview Process Short online survey (~15 minutes) Initial call (30-45 minutes) with founders Take-home coding and ML exercise (target ~8 hours) Onsite or virtual technical interviews with CEO, CTO, and engineering team — ML system design, research thinking, production engineering Offer Logistics Onsite preferred in San Mateo — Bay Area candidates willing to commute considered US work authorization required — no visa sponsorship or relocation assistance available Shortlisted candidates will be contacted by David Joseph & Co. , the recruiting partner managing this search on behalf of Hestus.
