Machine Learning Engineer, Robot Learning, Loco-Manipulation (Robotics)

Location: Columbus, Ohio, United States

Company

hirify.global develops AI-driven robotic systems that combine perception, reasoning, and control for real-world heavy-manufacturing applications.

What you will do

• Build the robot-learning stack, including training infrastructure, data pipelines, simulation environments, model architectures, and deployment workflows.
• Develop ML infrastructure for training pipelines, experiment tracking, data versioning, and reproducible sim-to-real workflows.
• Train robot policies for manipulation, locomotion, and whole-body control using behavioral cloning, diffusion and flow-matching action generation, and reinforcement-learning fine-tuning.
• Deploy models on physical robots through phased production rollouts and use real-world execution data for continuous improvement.
• Collaborate with mechanical, perception, and robotics engineers and manufacturing domain experts.

Requirements

• Master’s or Ph.D. degree in robotics, mechanical engineering, electrical engineering, computer science, or a related field, or equivalent experience.
• At least 2 years of hands-on robot-learning experience, including training and deploying policies on real robot hardware.
• Experience with simulation environments, domain randomization, sim-to-real transfer, and debugging policy failures on physical robots.
• Implementation experience with diffusion-based or flow-matching action policies and action chunking.
• Experience applying reinforcement learning to robotics on real hardware, plus strong Python, PyTorch, and production ML-infrastructure skills.
• Practical experience with NVIDIA Isaac Sim, Isaac Lab, MuJoCo, or an equivalent platform.

Nice to have

• Edge inference experience with TensorRT, ONNX, FP16, or INT8 quantization.
• Visual self-supervised representation learning for robotics or 3D-vision tasks.
• Legged-robot or whole-body-control experience, including locomotion and manipulation on floating-base robots.
• Physics-informed ML and hybrid models constrained by known physics.
• Experience building ML pipelines or infrastructure in a team setting.

Culture & Benefits

• Daily free lunch.
• Flexible paid time off.
• Medical, dental, and vision coverage.
• Six weeks of fully paid parental leave, with an additional six to eight weeks for birthing parents.
• 401(k) retirement plan through Empower.
• Employee referral bonuses and an inclusive environment that values diverse ideas.