Machine Learning Applied Researcher

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.

Responsibilities

• 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

Requirements

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.

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

Skills

• Experience with multimodal AI
• Strong programming skills (Python, R, etc.)
• Experience with machine learning frameworks (TensorFlow, PyTorch, etc.)
• Knowledge of natural language processing, computer vision, and/or signal processing

Benefits

• Competitive compensation package
• Flexible working hours
• Opportunities for professional growth and development
• Collaborative and inclusive workplace culture

Pay

Competitive salary based on experience and qualifications

Schedule

Full-time, remote work option available