Machine Learning Engineer, Perception

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Machine Learning Engineer, Perception in USA new

Path Robotics
Full time
Email

USA
10/31/2026
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Remote

Responsibilities

Implement, validate, and iterate on machine learning algorithms for weld perception, including point cloud registration, seam detection, and joint geometry estimation.
Build and maintain training and evaluation data pipelines using annotated 3D scan data, synthetic data generation, and structured dataset management.
Run model evaluation experiments, analyze failure modes and false-positive/false-negative rates, and benchmark registration accuracy.
Integrate trained models into production ROS-based robotics services with low-latency inference and deployed-cell compatibility.
Design and lead perception experiments involving transformer-based and geometric feature-learning architectures across structured-light, RGB, and stereo sensors.
Develop real-time seam-tracking systems using sensor fusion and probabilistic state estimation such as Kalman filtering.
Own the ML lifecycle from dataset design and annotation strategy through training, benchmarking, and fleet deployment.
Architect distributed training and hyperparameter optimization workflows and guide data acquisition, annotation tooling, and synthetic-versus-real scan strategies.
Write tested Python code, document methods and results, participate in reviews, and mentor engineers across levels.

Requirements

Master's or Ph.D. in computer science, robotics, or a related field such as computer vision, machine learning, or perception; a bachelor's degree with strong production ML experience is also considered.
3+ years of experience for experienced roles or 7+ years for senior/staff roles in real-world robotics or industrial machine learning.
Strong Python fluency and hands-on PyTorch experience training, evaluating, and deploying deep learning models in production.
Experience with 3D point cloud data and libraries such as Open3D, including surface segmentation, spatial queries, and point-wise labeling.
Familiarity with 3D deep learning architectures such as PointNet++, GeoTransformer, or similar transformer-based or graph-based approaches for geometric data.
Experience integrating machine learning models into production robotics services within ROS-based and containerized deployment environments.
Senior and staff candidates should have led end-to-end ML projects from dataset design through fleet deployment and architected distributed training and hyperparameter optimization workflows.

Benefits

Daily free lunch.
Flexible paid time off.
Comprehensive medical, dental, and vision coverage.
Six weeks of fully paid parental leave, plus an additional six to eight weeks for birthing parents.
401(k) retirement plan through Empower.
Employee referral bonuses.

Path Robotics

Path Robotics builds AI-driven robotic welding systems that autonomously plan and execute welds for metal fabrication and industrial manufacturers. The privately held company, founded in 2014 and headquartered in Columbus, Ohio, sells turnkey welding cells and software with support services, and ...

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