Machine Learning Engineer Perception

3 days agoColumbus, Ohio or Remote Remote Ai Jobs by Path Robotics

Skills

Computer Vision Containerization Deep Learning Distributed Training Geotransformer Hyperparameter Optimization Kalman Filtering Machine Learning Open3d Point Cloud Pointnet Python Pytorch Ros Sensor Fusion Spatial Query Surface Segmentation

Candidate Availability

Remote · Columbus · Required

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will develop, validate, and deploy machine-learning perception algorithms for weld tasks such as point-cloud registration, seam detection, and joint-geometry estimation. You will build data pipelines, evaluate models, integrate models into ROS-based services, and document your work. Depending on level, you may lead perception research, distributed training, data strategy, fleet deployment, and engineer mentoring.

Requirements

Master's or Ph.D. in computer science, robotics, computer vision, machine learning, perception, or a related field; or a bachelor's degree with strong production ML experience
3+ years of real-world robotics or industrial ML experience for experienced roles, or 7+ years for senior or staff roles
Python fluency and hands-on PyTorch experience
Experience training, evaluating, and deploying deep-learning models in production
Experience with 3D point-cloud data and Open3D
Knowledge of surface segmentation, spatial queries, and point-wise labeling
Familiarity with PointNet++, GeoTransformer, or similar geometric deep-learning architectures
Experience integrating ML models into ROS-based robotics services and containerized environments
For senior or staff roles, experience leading end-to-end ML projects, distributed training, and hyperparameter optimization

Responsibilities

Implement and validate machine-learning algorithms for weld perception tasks
Build and maintain training and evaluation data pipelines
Run model evaluation experiments, analyze failure modes, and communicate findings
Integrate trained models into ROS-based robotics services
Write tested Python code and maintain documentation
Lead advanced perception-algorithm research and production deployment
Design real-time perception systems using sensor fusion and probabilistic state estimation
Own the ML lifecycle from dataset design through fleet deployment
Architect distributed training and hyperparameter-optimization workflows
Mentor engineers on perception systems and ML methodology

Benefits