Machine Learning Engineer, Perception

Path Robotics · Remote · US only

US onlyExperience not statedPublished 30 October 2026Looks fresh

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First recorded by Psst: 31 October 2026. Sign in with Google to continue to the employer. A free account is enough.

The 20-second read

Experience
Experience not stated
Where you can live
US only
Skills and tools
python, machine learning, documentation
Degree or licence
Mentioned (master's)

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Job details

Where you can work
United States
Employment type
Not stated by the employer
Advertised pay
Not stated by the employer
Experience
Experience not stated
Employer publication date
30 October 2026
First recorded by Psst
31 October 2026
Last checked at the source
31 October 2026

About the job

Build the Path Forward

At 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.

Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.

We'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.

What You’ll Do

Experienced

  • Implement, 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.
  • Build 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.
  • Run 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.
  • 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; participate actively in code and experiment reviews; and maintain clear documentation of methods, parameters, and results.

Senior/Staff

  • Lead 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.
  • 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 such as during-weld seam tracking, applying sensor fusion with probabilistic state estimation (e.g., Kalman filtering) to achieve robust weld performance.
  • Define 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.
  • Architect distributed training and hyperparameter optimization workflows; drive strategy for data acquisition, annotation tooling, and synthetic vs. real scan data usage.
  • Mentor engineers across levels, providing technical leadership on perception systems and ML methodology.

Who You Are

  • 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

Why You’ll Love Working Here

  • Daily free lunch to keep you fueled and connected with the team
  • Flexible PTO so you can take the time you need, when you need it
  • 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—help us grow our team!

Who We Are

At 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.

If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact [email protected]. We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.

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