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Machine Learning Engineer, Perception

Path Robotics Columbus, OH

Columbus, OH

Today

Full time Artificial Intelligence Computer Vision Computer Vision Ml

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Job Description

Machine Learning Engineer, Perception builds weld perception for embodied robotics through computer vision, deep learning, and production deployment.

Responsibilities

Implement, validate, and iterate on ML algorithms for weld perception tasks including point cloud registration, seam detection, and joint geometry estimation, expanding coverage across joint types and part geometries.
Build and maintain data pipelines for training and evaluation, including annotated 3D scan ingestion, synthetic data generation, and structured dataset management for iterative improvement.
Run rigorous model evaluation experiments with failure mode analysis, FP/FN rate characterization, and benchmarking against quantitative registration accuracy thresholds; communicate findings to guide next steps.
Integrate trained models into production ROS-based robotics services, ensuring low-latency inference and compatibility with deployed cell configurations.
Write clean, well-tested Python code; participate in code and experiment reviews; maintain clear documentation of methods, parameters, and results.
Lead research, development, and production deployment of advanced perception algorithms covering point cloud registration, seam detection, and real-time in-process tracking across structured light, RGB, and stereo sensors.
Design and lead experiments evaluating state-of-the-art deep learning models, including transformer-based and geometric feature learning architectures.
Design and lead real-time perception systems for during-weld seam tracking, using sensor fusion with probabilistic state estimation (e.g., Kalman filtering) to support robust weld performance.
Own the end-to-end ML lifecycle, from dataset design and annotation strategy through training, benchmarking, and fleet deployment, using clear go/no-go evaluation frameworks.
Architect distributed training and hyperparameter optimization workflows; drive strategy for data acquisition, annotation tooling, and synthetic vs. real scan usage.
Mentor engineers across levels by providing technical leadership on perception systems and ML methodology.

Requirements

Master’s or Ph.D. in CS, Robotics, or related field (Computer Vision, ML, or Perception); Bachelor’s with strong production ML experience also considered.
3+ years (Experienced) / 7+ years (Senior/Staff) in real-world robotics or industrial ML.
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 geometric concepts like 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 on geometric data.
Comfort integrating ML models into production robotics services within ROS-based architectures and containerized deployment environments.
Senior/Staff: Demonstrated track record leading end-to-end ML projects from dataset design through fleet deployment with rigorous go/no-go frameworks; experience architecting distributed training and hyperparameter optimization workflows.

Technologies

Python
PyTorch
Open3D
ROS
Kalman filtering
PointNet++
GeoTransformer
Transformer-based architectures
Graph-based approaches
Containerized deployment environments
Structured light
RGB
Stereo sensors

Benefits

Daily free lunch
Flexible PTO
Comprehensive medical, dental, and vision coverage
6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
401(k) retirement plan through Empower
Generous employee referral bonuses

Location: Columbus, OH (onsite) | Minimum experience: 3 years

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