Automotive Research Engineer

Akkodis; Warren (MI); On-site; USD 66,124 - 79,900; Full time

Job summary

Akkodis is recruiting a Research Engineer for an automotive manufacturer in the Milford, MI area to develop HD maps for autonomous driving and to build scalable data pipelines for telemetry, sensor and geospatial data.

The role focuses on processing large-scale data to extract lane-level geometry and map features, while researching ML, computer vision, localization, and mapping algorithms and evaluating map quality for integration into autonomous driving research platforms.

Qualifications

• PhD in CS, EE, Robotics or related field required.
• Strong Python programming and ML/CV background.
• Experience with PySpark and Databricks on large datasets.

Responsibilities

• Develop HD maps for autonomous driving applications.
• Build scalable data pipelines for telemetry, sensor, and geospatial data.
• Research and prototype ML, CV, localization, and mapping algorithms.
• Collaborate with cross-functional teams to integrate outputs into research platforms.

Skills

Python

Deep Learning

Computer Vision

Localization

Education

PhD in CS/EE/Robotics

Tools

PySpark

Databricks

Job description

Akkodis is recruiting for a Research Engineer for an automotive manufacturer in the Milford, MI area with a pay range of $48 an hour to $58 an hour depending on education, experience and location. This candidate 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.

• Large Scale Telemetry and Crowdsource Data Analysis
• Geospatial Data Analysis
• Advanced Research & Proof of concept

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.

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.

Equal Opportunity Employer/Veterans/Disabled

Military connected talent encouraged to apply

• Benefit offerings available for our associates include medical, dental, vision, life insurance, short-term disability, additional voluntary benefits, 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.

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

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