Machine Learning Engineer, Perception

Path Robotics

. Implement, validate, and iterate on machine learning algorithms for weld perception tasks, including point cloud registration, seam detection, and joint geometry estimation .

Posted 10/30/2026full-timeRemote • Ohio • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in implementing and deploying machine learning algorithms for perception tasks in robotics, with a strong focus on Python programming and 3D point cloud data processing. Proven ability to lead end-to-end ML projects and mentor engineering teams in advanced ML methodologies.

Highest-signal resume keywords

Machine Learning Algorithm ImplementationPython Programming3D Point Cloud Data ProcessingROS-Based Robotics IntegrationDeep Learning Model Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningPoint Cloud RegistrationSeam DetectionJoint Geometry EstimationModel EvaluationHyperparameter OptimizationData Pipeline ManagementTransformer-Based ArchitecturesGeometric Feature Learning

Soft Skills

Technical LeadershipMentoringCollaboration

Tools & Technologies

PythonPyTorchOpen3DROSKalman Filtering

Industry Keywords

RoboticsComputer VisionIndustrial MLSynthetic Data GenerationReal-Time Perception Systems

Tech Stack

Tools & technologies

CloudPythonPyTorch

About the role

Key responsibilities & impact

Implement, validate, and iterate on machine learning algorithms for weld perception tasks, including point cloud registration, seam detection, and joint geometry estimation
Build and maintain data pipelines for annotated 3D scan data ingestion, synthetic data generation, and structured dataset management
Run model evaluation experiments, failure mode analysis, FP/FN rate characterization, and benchmarking against quantitative registration accuracy thresholds
Integrate trained models into production ROS-based robotics services for low-latency inference and deployed cell compatibility
Write clean, well-tested Python code; participate in code and experiment reviews; document methods, parameters, and results
Lead research, development, and production deployment of perception algorithms across structured light, RGB, and stereo sensors
Design and lead experiments evaluating transformer-based and geometric feature learning architectures
Design and lead real-time perception systems, including during-weld seam tracking and sensor fusion with probabilistic state estimation such as Kalman filtering
Own the end-to-end ML lifecycle from dataset design and annotation strategy through training, benchmarking, and fleet deployment
Architect distributed training and hyperparameter optimization workflows; drive data acquisition, annotation tooling, and synthetic versus real scan data strategy
Mentor engineers across levels and provide technical leadership on perception systems and ML methodology

Requirements

What you’ll need

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, 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
Comfortable 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

Benefits

Comp & perks

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