Senior Manager, Robotics Customer Trainer
Medtronic
Staff ML Engineer, Robotics
Diligent Robotics
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteJob Level
Lead
Tech Stack
PythonPyTorchTensorflow
About the role
- Develop and deploy ML models for perception/navigation tasks such as object detection, semantic segmentation, tracking, scene understanding, localization, and path prediction.
- Design and implement sensor fusion and mapping pipelines combining vision, depth, LIDAR, IMU, and other signals for robust perception and navigation in dynamic spaces.
- Build real-time ML inference pipelines optimized for robotic hardware and embedded compute.
- Setup data collection, labeling strategies, dataset curation, and synthetic data augmentation for training and evaluation.
- Establish metrics, benchmarks, and test frameworks to validate ML models in both simulation and real-world environments.
- Collaborate with robotics software engineers to integrate perception and navigation intelligence into autonomy stacks.
- Work with operations to analyze field data, diagnose performance gaps, and iterate on model improvements.
- Contribute to long-term ML and perception and navigation architecture decisions, influencing the roadmap for future robots.
- Mentor junior ML engineers and contribute to building strong applied ML best practices within the team.
Requirements
- Master’s or PhD in Computer Science, Robotics, Machine Learning, or related field.
- 8+ years of experience in applied machine learning, computer vision, or robotics perception.
- Strong background in deep learning frameworks (PyTorch, TensorFlow, JAX).
- Hands-on experience with real-time perception/navigation tasks (detection, tracking, segmentation,path planning).
- Expertise in one or more sensor modalities: RGB/depth cameras, LIDAR, radar, or multimodal fusion.
- Experience deploying ML models on edge/embedded hardware (e.g., Jetson, TPU, ARM-based platforms).
- Familiarity with SLAM, mapping, and navigation pipelines.
- Solid software engineering skills in Python and C++ for ML system integration.
- Proven ability to take ML models from research prototype to production deployment.
- Strong debugging skills for diagnosing ML performance gaps in fielded systems.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningcomputer visiondeep learningsensor fusionreal-time inferencedata collectiondataset curationsynthetic data augmentationdebuggingproduction deployment
Soft skills
mentoringcollaborationproblem-solvingcommunicationleadership
Certifications
Master’s degreePhD
