Machine Learning Engineer, Perception

Path Robotics • Columbus, OH

5d

About The Position

Path Robotics is seeking Machine Learning Engineers to develop robotic welding solutions at the intersection of welding science and artificial intelligence. The role focuses on perception using computer vision, deep learning, and Python, with openings at experienced (L3/L4), senior (L5), and staff (L6) levels.

Experienced engineers implement, validate, and improve machine learning algorithms for weld perception, including point cloud registration, seam detection, and joint geometry estimation. They build data pipelines for annotated 3D scans, synthetic data, and structured datasets; evaluate model performance and failure modes; integrate models into production ROS-based services; and write, test, review, and document Python code and experiments.

Senior and staff engineers lead development and deployment of advanced perception algorithms across structured-light, RGB, and stereo sensors. They design experiments for deep learning architectures, develop real-time perception and sensor-fusion systems, own the ML lifecycle from dataset strategy through fleet deployment, architect distributed training and hyperparameter optimization workflows, and mentor other engineers.

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.
• At least 3 years of experience for experienced-level roles, or at least 7 years for senior/staff roles, in real-world robotics or industrial ML.
• Strong Python skills 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.
• Ability to integrate ML models into production robotics services in ROS-based architectures and containerized deployment environments.

Nice To Haves

• For senior/staff roles, a demonstrated record of leading end-to-end ML projects from dataset design through fleet deployment using rigorous go/no-go frameworks.
• For senior/staff roles, experience architecting distributed training and hyperparameter optimization workflows.

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 for annotated 3D scans, synthetic data generation, and structured dataset management.
• Run model evaluation experiments, analyze failure modes and false-positive/false-negative rates, benchmark registration accuracy, and communicate results.
• Integrate trained models into production ROS-based robotics services while ensuring low-latency inference and compatibility with deployed cell configurations.
• Write clean, well-tested Python code; participate in code and experiment reviews; and document methods, parameters, and results.
• For senior/staff roles, lead research, development, and production deployment of perception algorithms across structured-light, RGB, and stereo sensors.
• For senior/staff roles, design and lead experiments evaluating deep learning models, including transformer-based and geometric feature-learning architectures.
• For senior/staff roles, design and lead real-time perception systems, including during-weld seam tracking and sensor fusion with probabilistic state estimation.
• For senior/staff roles, own the end-to-end ML lifecycle from dataset design and annotation strategy through training, benchmarking, and fleet deployment, using clear go/no-go frameworks.
• For senior/staff roles, architect distributed training and hyperparameter optimization workflows and set strategy for data acquisition, annotation tools, and synthetic versus real scan data.
• For senior/staff roles, mentor engineers and provide technical leadership on perception systems and ML methodology.

Benefits

• Daily free lunch
• Flexible paid time off
• Comprehensive medical coverage
• Dental coverage
• Vision coverage
• Six weeks of fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
• 401(k) retirement plan through Empower
• Employee referral bonuses

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level