{"id":3548822,"url":"https://alion.io/job/path-robotics-machine-learning-engineer-perception","title":"Machine Learning Engineer, Perception","company":{"id":48166,"name":"Path Robotics","domain":"path-robotics.com","url":"https://alion.io/company/path-robotics","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":78,"open_postings":19,"ghost_share":0,"stale_share":0.684,"repost_share":0,"time_to_fill_p50_days":62,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Columbus, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":142000,"max_usd":269000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":370},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Embodied AI","optional":false},{"name":"Machine Learning","optional":false},{"name":"Open3D","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"ROS","optional":false},{"name":"Sensor Fusion","optional":false},{"name":"Synthetic Data","optional":false}],"status":"live","first_seen_at":"2026-10-30T19:54:56Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-01T03:25:00Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Build the Path Forward\nAt Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.\nBig, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.\nWe're seeking passionate CV/ML Engineers to join our team at the intersection of welding science and artificial intelligence. We currently have experienced (L3/L4), senior (L5) and staff (L6) level openings within the team. You'll use your skills in problem solving, computer vision, deep learning, and Python programming to tackle challenges in our field alongside our talented teams.\nWhat You’ll Do\nExperienced:\nImplement, validate, and iterate on machine learning algorithms for weld perception tasks, including point cloud registration, seam detection, and joint geometry estimation, progressively expanding coverage across joint types and part geometries.\nBuild and maintain data pipelines for training and evaluating perception models, spanning annotated 3D scan data ingestion, synthetic data generation, and structured dataset management for iterative model improvement.\nRun rigorous model evaluation experiments, including failure mode analysis, FP/FN rate characterization, and benchmarking against quantitative registration accuracy thresholds, and communicate findings clearly to guide next steps.\nIntegrate trained models into production ROS-based robotics services, ensuring low-latency inference and compatibility with deployed cell configurations.\nWrite clean, well-tested Python code; participate actively in code and experiment reviews; and maintain clear documentation of methods, parameters, and results.\nSenior/Staff:\nLead research, development, and production deployment of advanced perception algorithms spanning point cloud registration, seam detection, and real-time in-process tracking across structured light, RGB, and stereo sensors.\nDesign and lead experiments evaluating state-of-the-art deep learning models, including transformer-based and geometric feature learning architectures\nDesign and lead real-time perception systems such as during-weld seam tracking, applying sensor fusion with probabilistic state estimation (e.g., Kalman filtering) to achieve robust weld performance.\nDefine and own the end-to-end ML lifecycle, from dataset design and annotation strategy through training, benchmarking, and fleet deployment, with clear go/no-go evaluation frameworks.\nArchitect distributed training and hyperparameter optimization workflows; drive strategy for data acquisition, annotation tooling, and synthetic vs. real scan data usage.\nMentor engineers across levels, providing technical leadership on perception systems and ML methodology.\nWho You Are\nMaster's or Ph.D. in CS, Robotics, or related field (Computer Vision, ML, or Perception); Bachelor's with strong production ML experience also considered. \n3+ years (Experienced) / 7+ years (Senior/Staff) in real-world robotics or industrial ML.\nStrong Python fluency and hands-on PyTorch experience, including training, evaluating, and deploying deep learning models in production.\nExperience with 3D point cloud data and libraries such as Open3D, including geometric concepts like surface segmentation, spatial queries, and point-wise labeling.\nFamiliarity with 3D deep learning architectures such as PointNet++, GeoTransformer, or similar transformer-based or graph-based approaches on geometric data.\nComfortable integrating ML models into production robotics services within ROS-based architectures and containerized deployment environments.\nSenior/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\nWhy You’ll Love Working Here\nDaily free lunch to keep you fueled and connected with the team\nFlexible PTO so you can take the time you need, when you need it\nComprehensive medical, dental, and vision coverage\n6 weeks fully paid parental leave, plus an additional 6-8 weeks for birthing parents (12-14 weeks total)\n401(k) retirement plan through Empower\nGenerous employee referral bonuses-help us grow our team!\nWho We Are\nAt Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.\nIf you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact . We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. 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