Staff Machine Learning Engineer - Robotics Simulation

Antioch; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Antioch is seeking a Member of Technical Staff, Machine Learning to advance a core ML team building faithful simulations of physical systems. The role focuses on combining physical models with learning from real data, and shipping production capabilities with engineering and platform teams.

You’ll work on sim-to-real gaps, world and diffusion models, and data-driven calibration to improve fidelity and customer outcomes.

Qualifications

• Deep applied ML experience.
• Strong foundations in statistics, optimization, and experimental design.
• Experience modeling physical systems in robotics, controls, or system identification.
• Strong Python and software engineering skills for data pipelines and evaluation.
• Experience turning messy real-world telemetry into usable datasets and measurable improvements.
• Strong collaboration across disciplines, customer needs, and time to ship.

Responsibilities

• Measure sim-to-real and real-to-sim gaps with benchmarks and uncertainty estimates.
• Develop and ship calibration methods combining physics models and ML.
• Build self-serve workflows to ingest sensor telemetry and calibrate digital twins.
• Establish a continuous data feedback loop to improve models and platform capabilities.
• Advance Antioch's learned simulation roadmap with world models and diffusion models.
• Build and ship foundational ML models, pipelines, and tools.

Job description

Antioch is seeking a Member of Technical Staff, Machine Learning to advance a core ML team building faithful simulations of physical systems. The role focuses on combining physical models with learning from real data, and shipping production capabilities with engineering and platform teams.

You’ll work on sim-to-real gaps, world and diffusion models, and data-driven calibration to improve fidelity and customer outcomes.