- Company Name
- Diligent Robotics
- Job Title
- Staff ML Engineer, Robotics
- Job Description
-
Job title: Staff ML Engineer, Robotics
Role Summary: Lead the development, deployment, and optimization of machine‑learning models that power perception and navigation for service robots, ensuring robust, real‑time performance in safety‑critical, dynamic human environments.
Expactations: Deliver end‑to‑end ML solutions from research to production, design scalable sensor‑fusion pipelines, integrate models with autonomy stacks, validate performance in simulation and field, mentor junior engineers, and shape long‑term perception architecture.
Key Responsibilities:
- Develop and deploy perception and navigation models (object detection, semantic segmentation, tracking, scene understanding, localization, path prediction).
- Design sensor‑fusion and mapping pipelines combining vision, depth, LIDAR, IMU, and other modalities for robust real‑time inference.
- Build and optimize inference pipelines for robotic hardware (Jetson, TPU, ARM).
- Set up data collection, labeling, dataset curation, and synthetic augmentation.
- Establish metrics, benchmarks, and test frameworks in simulation and real‑world deployments.
- Collaborate with robotics software engineers to integrate perception intelligence into autonomy stacks.
- Analyze field data with operations, diagnose gaps, and iterate on model improvements.
- Influence long‑term ML and perception architecture decisions.
- Mentor junior ML engineers and establish applied ML best practices.
Required Skills:
- 8+ years in applied ML, computer vision, or robotics perception.
- Deep learning frameworks: PyTorch, TensorFlow, JAX.
- Real‑time perception/navigation expertise (detection, tracking, segmentation, path planning).
- Sensor modality proficiency (RGB/depth cameras, LIDAR, radar, multimodal fusion).
- Deployment on edge/embedded hardware (Jetson, TPU, ARM).
- Knowledge of SLAM, mapping, navigation pipelines.
- Strong software engineering in Python and C++.
- Proven track record of moving models from prototype to production.
- Robust debugging and performance‑gap analysis.
Required Education & Certifications:
- Master’s or PhD in Computer Science, Robotics, Machine Learning, or related field.