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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

Build weld perception systems for embodied robotics, turning point cloud and sensor data into production-ready deep learning capabilities.

Responsibilities

Implement, validate, and iterate on machine learning 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 evaluating perception models, 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; contribute to code and experiment reviews; maintain clear documentation of methods, parameters, and results.
Lead research, development, and production deployment of advanced perception algorithms for 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 and probabilistic state estimation (for example, Kalman filtering) to achieve robust weld performance.
Define and own the end-to-end ML lifecycle: dataset design and annotation strategy, training, benchmarking, and fleet deployment with clear go/no-go evaluation frameworks.
Architect distributed training and hyperparameter optimization workflows; drive strategy for data acquisition, annotation tooling, and synthetic versus real scan data 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 a 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, including 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 only: Demonstrated track record leading end-to-end ML projects from dataset design through fleet deployment with rigorous go/no-go frameworks, plus 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 to keep you fueled and connected with the team
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)

Experience: 3+ years (Experienced) / 7+ years (Senior/Staff)

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