{"id":1230902,"url":"https://alion.io/job/archetype-ai-ai-researcher","title":"AI Researcher","company":{"id":1814726,"name":"Archetype AI","domain":"archetypeai.io","url":"https://alion.io/company/archetypeai","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Kula","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Mateo, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":160000,"max_usd":307000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1268},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Self-Supervised Learning","optional":false},{"name":"Contrastive Learning","optional":true},{"name":"Physical AI","optional":true}],"status":"live","first_seen_at":"2026-09-24T14:38:56Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-24T16:50:55Z","board_verified":true,"closed_at":null,"days_open":30,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":30},"description":"About Us\nAt Archetype AI, we’re building the world’s first physical AI platform to bring artificial intelligence into the real world. Our foundation model, Newton, understands the physical world through objective sensor data and generates real-time insights into complex physical behaviors, from industrial machinery and systems to wearable devices and smart environments.\nFormed by a high-caliber team from Google and backed by one of Silicon Valley’s most renowned venture funds, Archetype AI is at Series A and rapidly advancing its technology for the next big leap. This is a unique opportunity to join an exciting, fast-growing AI team based in the heart of Silicon Valley.\nAbout the Role\nWe are building the next generation of foundation models for real-world sensor data. Our goal is to develop AI systems that can learn rich representations of complex environments from diverse physical measurements, including vibration, temperature, electrical signals, gases, video, and other sensor modalities, and use those representations to understand and reason about the physical world.\nWe are looking for an AI Researcher to design, train, and interpret large-scale models that learn directly from raw sensor streams. This role combines deep learning research, large-scale experimentation, and hands-on system building, with the opportunity to shape core technology used across multiple real-world applications.\nYou will work on problems at the intersection of representation learning, multimodal learning, foundation models, and physical-world sensing.\nWhat You’ll Own\nDesign and train foundation models for sensor data, including multimodal architectures combining non-visual sensing modalities.\n\nDevelop new approaches for representation learning, multimodal alignment, and self-supervised learning from raw sensor streams.\n\nDevelop methods for adapting pretrained models to new datasets, sensing modalities, environments, and customer use cases, understanding and navigating trade-offs between data availability, model capacity, and performance.\n\nIdentify model limitations, diagnose failure modes, and design experiments that drive measurable improvements.\n\nCollaborate closely with engineers and product teams to translate research advances into production systems.\n\nKey Qualifications\n8+ years of experience developing advanced ML/AI systems, with a focus on real-world sensor data.\n\nStrong expertise in modern deep learning architectures, especially transformers, representation learning, and large-scale model training.\n\nStrong research and experimentation skills, including designing and evaluating new approaches.\n\nExcellent programming skills in Python, with deep learning frameworks such as PyTorch.\n\nAbility to move quickly from idea → experiment → working prototype.\n\nComfortable working in a fast-paced, multidisciplinary environment with a distributed team.\n\nExcellent written and verbal communication skills.\n\nNice to Have\nFamiliarity with LLMs.\n\nExperience with self-supervised or contrastive learning for large unlabeled datasets.\n\nExperience with large-scale training infrastructure or distributed training 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