AI Researcher

Pivots Hiring; San Mateo (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Archetype AI is shaping the next generation of foundation models for real-world sensor data. We seek an AI Researcher to design, train, and interpret large-scale models that learn from raw sensor streams and multimodal inputs, enabling systems that reason about the physical world.

Join a fast-growing Silicon Valley team, bridging research and production with collaboration across engineering and product teams to deploy core AI technologies in real-world applications.

Qualifications

• 8+ years of experience building ML/AI systems with real-world sensor data.
• Deep learning expertise in transformers and representation learning.
• Strong research and experimentation skills with new approaches.
• Proficient in Python and PyTorch for experimentation.
• Ability to move quickly from idea to prototype.
• Experience working in fast-paced, distributed teams.
• Excellent written and verbal communication.

Responsibilities

• Design and train foundation models for sensor data, including multimodal architectures.
• Develop representation learning and self-supervised methods for raw sensor streams.
• Adapt pretrained models to new datasets and sensing modalities with trade-offs.
• Identify failures and design experiments to drive improvements.
• Collaborate with engineers and product teams to deploy research to production.

Skills

ML/AI systems

Transformers

Representation learning

Large-scale model training

Python

PyTorch

Experimentation

Communication skills

Job description

About Us

At 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.

Formed 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.

About the Role

We 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.

We 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.

You will work on problems at the intersection of representation learning, multimodal learning, foundation models, and physical-world sensing.

What You’ll Own

• Design and train foundation models for sensor data, including multimodal architectures combining non-visual sensing modalities.
• Develop new approaches for representation learning, multimodal alignment, and self-supervised learning from raw sensor streams.
• Develop 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.
• Identify model limitations, diagnose failure modes, and design experiments that drive measurable improvements.
• Collaborate closely with engineers and product teams to translate research advances into production systems.

Key Qualifications

• 8+ years of experience developing advanced ML/AI systems, with a focus on real-world sensor data.
• Strong expertise in modern deep learning architectures, especially transformers, representation learning, and large-scale model training.
• Strong research and experimentation skills, including designing and evaluating new approaches.
• Excellent programming skills in Python, with deep learning frameworks such as PyTorch.
• Ability to move quickly from idea → experiment → working prototype.
• Comfortable working in a fast-paced, multidisciplinary environment with a distributed team.
• Excellent written and verbal communication skills.

Nice to Have

• Familiarity with LLMs.
• Experience with self-supervised or contrastive learning for large unlabeled datasets.
• Experience with large-scale training infrastructure or distributed training frameworks.