Job Title: Software Engineer – Fleet Mapping (Python / Machine Learning)

Location: Foster City, CA (Onsite – 3 Days per Week)
Duration: 6-Month Contract
Interview Process: 2–3 Rounds (30–45 Minutes Each)

Job Description

We are seeking an experienced Software Engineer to join an AI-focused Fleet Mapping team working on advanced autonomous vehicle mapping technologies.

The team focuses on offline mapping, processing vehicle sensor data and transforming it into high-definition (HD) maps used by autonomous vehicles. These maps contain multiple layers of geometric and semantic information that help self-driving vehicles understand their surroundings and navigate safely.

The ideal candidate will have strong Python programming skills, hands-on Machine Learning experience, and a background in Computer Vision, Robotics, or Autonomous Vehicle technologies.

Key Responsibilities

• Develop, implement, and support Machine Learning solutions for automated map generation and mapping feature development.

• Design, train, and improve ML models for semantic detection and classification of map elements.

• Build, curate, validate, and maintain datasets for model training and evaluation.

• Integrate ML models into large-scale mapping systems and automated pipelines.

• Develop automation solutions to reduce manual map labeling and improve mapping efficiency.

• Collaborate with validation teams to establish and execute model validation workflows.

• Analyze vehicle sensor data to support the development of accurate geometric and semantic maps.

• Improve model performance, scalability, and reliability for autonomous driving applications.

Required Skills

• Strong hands-on experience with Python programming.

• Solid understanding of Machine Learning concepts and algorithms.

• Experience developing, training, and evaluating ML models.

• Hands-on experience with PyTorch.

• Experience working with NumPy and related ML/data processing libraries.

• Understanding of ML workflows, including dataset preparation, model training, validation, and evaluation.

• Strong problem-solving and analytical skills.

Preferred Qualifications

• Master's degree in Robotics, Machine Learning, Computer Vision, or a related technical field.

• Experience in Computer Vision, 3D Computer Vision, or Perception Systems.

• Background in Robotics or Autonomous Vehicle technologies.

• Experience with object detection, classification, tracking, and semantic segmentation.

• Familiarity with HD Mapping, Fleet Mapping, or Semantic Mapping.

• Experience processing vehicle sensor data and developing mapping solutions.

• Experience automating mapping workflows and reducing manual data labeling.

Project Overview

The team works on perception-related challenges involving object detection, classification, tracking, and environmental understanding.

The mapping system generates geometric and semantic 3D maps containing important road features, including:

• Road lanes and lane boundaries

• Crosswalks and pedestrian crossings

• Traffic signs and traffic controls

• Road geometry and other driving-related features

The primary objective is to scale high-definition map creation through Machine Learning and automation while maintaining accuracy and quality for autonomous driving applications.

Ideal Candidate

A Python-focused Software Engineer with practical Machine Learning model development experience and strong exposure to Computer Vision, Robotics, or Autonomous Vehicle technologies. Candidates who have worked on ML-powered mapping solutions, perception systems, or automated mapping pipelines will be highly preferred.

Interested candidates are encouraged to share their updated resumes.