Autonomous Driving Software Engineer

Position / Title: Autonomous Driving Research Engineer- Crowd-sourcing for Map Updates

Duration: 6 months/C2H

Location: Warren MI

Payrate Range: $50- $55/hour on W2; (The rate may be negotiable based on experience, education, geographic location, and other factors.

Job Description:

The Research Engineer will develop advanced methods and scalable data pipelines for creating, updating, and validating high-definition (HD) maps to support autonomous driving systems. The role focuses on processing large-scale vehicle telemetry, sensor, and geospatial data to extract lane-level road geometry, semantic map features, traffic-control elements, and other map attributes needed for localization, perception, planning, and decision-making. The engineer will research and prototype machine learning, computer vision, localization, and mapping algorithms, evaluate map quality and accuracy, and collaborate with cross-functional teams to integrate HD map outputs into autonomous driving research platforms.

Candidate Requirements:

• PhD degree in Computer Science, Electrical Engineering, Robotics (or Mechanical Engineering, Civil Engineering, or a related discipline). Good problem-solving skills and passion for autonomous driving technologies. Good knowledge or experience in automotive data science, machine learning, localization and mapping, robotics, autonomous driving, etc.
• Large-Scale Telemetry & Crowdsource Data Analysis: Analyze vast amounts of telemetry and crowdsource data collected from vehicles and systems to uncover hidden patterns and derive actionable insights.
• Geospatial data analysis and spatial resolution processing systems, such as H3 indexing.
• Deep Learning Model Research: Design, train, evaluate, and optimize state-of-the-art deep learning architectures and models using sensor data.
• Data Pipeline Development: Build and enhance robust data processing pipelines in large-scale distributed environments using Databricks, Python, and PySpark.
• Advanced Research & Proof of Concept (PoC): Analyze the latest AI/ML research papers and technology trends, developing and validating prototypes for integration into internal projects.
• Integrating research-phase models into production environments or establishing MLOps pipelines.

Minimum Qualifications

• Research Experience: Academic or industry research and development experience in Deep Learning, Computer Vision, or related AI/ML fields.
• Programming Skills: High proficiency in coding and algorithm implementation using Python.
• Big Data Tech Stack: Hands-on experience with large-scale data processing and cluster management utilizing PySpark and Databricks platforms.
• Domain Knowledge: Solid understanding of processing telemetry data, as well as large-scale time-series and unstructured data.

Equal Opportunity Employer/Veterans/Disabled

Benefit offerings available for our associates include medical, dental, vision, life insurance, short-term disability, additional voluntary benefits, an EAP program, commuter benefits, and a 401K plan. Our benefit offerings provide employees the flexibility to choose the type of coverage that meets their individual needs. In addition, our associates may be eligible for paid leave including Paid Sick Leave or any other paid leave required by Federal, State, or local law, as well as Holiday pay where applicable. Disclaimer: These benefit offerings do not apply to client-recruited jobs and jobs that are direct hires to a client.

To read our Candidate Privacy Information Statement, which explains how we will use your information, please visit https://www.akkodis.com/en/privacy-policy.

The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:

· The California Fair Chance Act

· Los Angeles City Fair Chance Ordinance

· Los Angeles County Fair Chance Ordinance for Employers

· San Francisco Fair Chance Ordinance