Senior Autonomous Vehicle Perception and Mapping Engineer

What You’ll Do:

Design, implement, test and deploy offline 3D reconstruction, lane line detection, and automatic mapping/map creation modules to generate high-quality annotations on Cloud Services from logged sensor data (Cameras, Lidars, Radars, GPS/IMU).

• Build and refine lane line annotation pipelines, applying the latest lane line detection and creation machine learning models to automate and scale map creation.
• Develop and improve pose estimation algorithms to support accurate localization, sensor fusion, and 3D scene reconstruction.
• Demonstrate project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution.
• Stay up to date with the latest developments in AI and ML for autonomous driving, 3D reconstruction, and automated mapping.
• Independently develop offline perception and mapping models or algorithms using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining documentation of created applications.
• Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows.
• Proactively assess current capabilities to identify areas for improvement, proposing solutions that align with core strategy and operation.
• Measure and track auto-labeling and map creation quality to meet internal customer requirements.
• Guide and produce information products, supporting visualization and data accessibility in a customer-centric manner.
• Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety.
• Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes.
• Provide technical guidance or business process expertise, technical leadership, coaching and mentoring to team members.

What You’ll Need to Succeed:

• Considered highly skilled and proficient in discipline; conducts complex, important work under minimal supervision and with wide latitude for independent judgment.
• Scope of Influence: Expected to drive alignment across team interfaces to the rest of the organization. Designs, maintains and owns team technical solutions and drives consensus. Mentors and guides engineers within the group.
• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrated competencies and technical proficiencies typically acquired through 6+ years of experience OR;
• Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrated competencies and technical proficiencies typically acquired through 3+ years of experience OR;
• Required Qualifications (some combination of the following skills):
  • Experience in lane line annotation creation or automatic mapping/map creation.
  • Familiarity with the latest lane line detection and creation machine learning models.
  • Familiarity with pose estimation.
  • Active Learning & Pseudo-labeling – Computer Vision, Deep Learning, Model training.
  • Two of the following: 2D/3D Object Detection, Tracking, Sensor Fusion, Semantic Segmentation, SLAM, BEV.
  • Scaled ML Operations (MLOps) and Tooling – ML Frameworks, experiment tracking, model registry, MLflow, Weights and Biases, ML Metrics and Evaluation / Quality.
  • Distributed machine learning frameworks – PyTorch, Lightning, Ray.
  • Model Data Curation – Parquet data processing (PyArrow, Daft, Pandas, etc).
  • Development Tools & Eco-System (at scale) – Proficiency in Python software development. Also, VDI and cloud-based development environments, CI Systems (GitHub Actions), and Docker.

Bonus Points!

• PPK/RTK (Post-Processed Kinematic / Real-Time Kinematic) GPS experience.
• GIS (Geographic Information Systems) experience.