Senior Machine Learning Engineer (Robotics & Physical AI)

Empathy Talent; New York (NY); On-site; USD 140,000 - 230,000; Full time

Benefits offered by this job

Equity

Job summary

Empathy Talent in New York City is assembling a rapid-iteration, production-grade ML infrastructure team to power autonomous robotics and physical AI applications. The role focuses on building scalable data platforms and training systems for multimodal datasets, with close collaboration from ML researchers and robotics engineers.

The team aims for high availability, efficiency, and real-world impact, operating in a fast-paced startup environment where ownership and technical excellence are

Qualifications

• Experience designing and operating large-scale data platforms (PB-scale preferred).
• Background building distributed ML training or inference systems.
• Experience with streaming, real-time data processing, and event-driven architectures.
• Comfortable owning infrastructure in a fast-moving startup environment with significant autonomy.
• Passion for solving complex engineering problems and building technology that operates in the physical world.
• Excited about robotics, automation, and applied AI.

Responsibilities

• Own and scale ML infra and data platform.
• Design systems for petabyte-scale multimodal data for training.
• Build distributed training infra, experiment tracking, and compute clusters.
• Develop high-performance pipelines for video and sensor data.
• Collaborate with ML researchers and robotics engineers to accelerate experiments.
• Ensure reliability, scalability and availability of ML infrastructure.

Skills

PB-scale data platforms

Distributed ML training

Streaming data

Real-time processing

Startup autonomy

Robotics/AI enthusiasm

Job description

Join an early-stage robotics company building industrial AI systems that are already operating in production environments across U.S. warehouses. The team is developing intelligent robots that automate mission-critical warehouse operations, with a strong focus on real-world deployment, rapid iteration, and continuous learning from production data.

This is a highly ambitious, fast-paced environment where engineering excellence and execution matter. The team values builders who enjoy solving difficult technical challenges and want to help shape the future of physical AI and intelligent automation.

Location: New York City (On-site)

What You\'ll Do

• Own and scale the company's machine learning infrastructure and data platform.
• Design systems capable of ingesting, processing, and serving petabyte-scale multimodal datasets for model training.
• Build and maintain distributed training infrastructure, experiment tracking systems, and compute cluster management.
• Develop high-performance data pipelines supporting video, sensor, and other large-scale robotics datasets.
• Partner closely with ML researchers and robotics engineers to accelerate experimentation and model development.
• Ensure reliability, scalability, and high availability of critical ML infrastructure.

What We're Looking For

• Strong experience designing and operating large-scale data platforms (PB-scale preferred).
• Background building distributed machine learning training or inference systems.
• Experience with streaming, real-time data processing, and event-driven architectures.
• Comfortable owning infrastructure in a fast-moving startup environment with significant autonomy.
• Passion for solving complex engineering problems and building technology that operates in the physical world.
• Excited about robotics, automation, and applied AI.

Preferred Qualifications

• Experience supporting autonomous vehicle, robotics, or other large-scale multimodal datasets.
• Hands-on experience with distributed ML training workloads (1,000+ GPU hours).
• Knowledge of video compression, codecs, and efficient video storage/retrieval systems.
• Familiarity with reinforcement learning, imitation learning, or vision-language-action (VLA) training pipelines.
• Experience integrating software with production hardware systems.

Compensation

• Equity

This is an excellent opportunity for someone who wants to build the infrastructure powering next-generation robotics and physical AI while working on technology that is already making an impact in real-world production environments.