Machine Learning Applied Researcher

Pivots Hiring; San Mateo (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Restaurant stipend

Job summary

Archetype AI is building the world’s first physical AI platform and seeks an experienced ML researcher to help develop multimodal foundation models grounded in real-world signals. You will work end-to-end—from problem formulation and experimental design to model development, evaluation, and deployment.

This role is ideal for someone highly self-directed, capable of rigorous scientific work, and excited to translate research advances into production systems for industrial environments.

Qualifications

• Self-directed and able to operate in ambiguous problem spaces.
• Strong scientific work: form hypotheses, design experiments, draw conclusions.
• Experience with end-to-end modeling (data, modeling, evaluation).
• Experience with productionizing ML models and deployments.
• Multimodal experience preferred.

Responsibilities

• Build multimodal foundation models incorporating time-series data with language, vision, and audio.
• Lead research efforts from problem definition through experimentation and evaluation.
• Own modeling work across data, modeling, and evaluation.
• Advance architectures and training for physical-world understanding and long-context reasoning.
• Scale experiments and modeling advances to production models for diverse industrial use cases.
• Contribute to research directions with potential for publication.

Skills

Self-directed

Experimental rigor

End-to-end modeling

Productionization

Multimodal experience

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 a new class of multimodal foundation models for the physical world. Our focus is on combining time series / sensor data, language, vision, audio, and other real-world signals into unified models that can understand complex systems, reason over long horizons, and support real-world tasks in industrial and physical environments.

We are looking for an experienced, researcher-oriented ML candidate to help build these systems end to end: from problem formulation and experimental design, to model development, evaluation, and deployment.

This role is intended for someone who is highly self-directed, can independently perform strong scientific work, and is excited to work on multimodal intelligence grounded in physical signals.

What You’ll Own

• Build and improve multimodal foundation models that incorporate time-series / sensor data alongside language, vision, audio, and related modalities.
• Drive research and modeling efforts from problem definition through experimentation and evaluation.
• Own modeling work across data, modeling, and evaluation.
• Advance model architectures and training strategies for physical-world understanding and long-context reasoning.
• Drive and scale research experiments and modeling advances to production models that power diverse use cases in complex industrial scenarios.
• Contribute to research directions with potential for publication.

Key Qualifications

• Self-directed and comfortable operating in ambiguous problem spaces.
• Able to independently perform strong scientific work, including forming hypotheses, designing experiments, and drawing sound conclusions.
• Experience with end-to-end modeling, including data, modeling, and evaluation.
• Experience with productionization or deployment of ML models.
• Multimodal experience preferred.
• Strong technical judgment and experimental rigor.

Why This Role Is Interesting

• Many important real-world systems cannot be understood from text or vision alone. Their behavior depends on signals that evolve over time: sensors, operating conditions, environment, and interactions across subsystems.
• You will have a unique opportunity to help shape a new generation of multimodal foundation models grounded in physical signals and real-world dynamics. The role offers a rare combination of deep research challenges, practical deployment impact, and the chance to contribute to a fast-emerging area of AI.