Crowd-sourcing for Map Updates

Akkodis is recruiting for a Crowd Sourcing Map Engineer for an automotive manufacturer in the Warren MI area. This is an onsite contract position with a pay range of $40 an hour to $52 an hour, depending on education, experience and location.

The project aims to leverage crowd -sourced vehicle sensor data collected from production vehicles to design and develop an HD map generation framework to support GM autonomous driving features. The framework will consume GNSS telemetry data , perception semantics data (e.g., lane lines, traffic signs, drivable space), and vehicle dynamics data (e.g., steering, velocity, yaw rate) from customer vehicles operating in the field within designated geofenced
areas.

The objectives of this project are to research, design, and implement a set of models and algorithms, together with an end -to-end data processing pipeline, to construct and maintain HD maps from crowd -sourced vehicle data. The framework will focus on:
1. Optimizing lane line extraction models based on GNSS telemetry data from fleets of vehicles.
2. Creating an end -to- end data processing pipeline from raw vehicle logs through map product generation.
3. Developing models and algorithms that leverage camera and perception semantics data to construct and refine lane -level HD maps and related map elements.
4. Performing system integration and map validation using a combination of simulation platforms and real -world in - vehicle tests.
5. Processing experiment data and creating technical documentation , including design documents, experiment reports, and integration guides.

The developed technologies will be used to support GM’s autonomous driving technology development to improve robustness, coverage, freshness, and customer experience.The project aims to leverage crowd -sourced vehicle sensor data collected from production vehicles to design and develop an HD map generation framework to support GM autonomous driving features. The framework will consume GNSS telemetry data , perception semantics data (e.g., lane lines, traffic signs, drivable space), and vehicle dynamics data (e.g., steering, velocity, yaw rate) from customer vehicles operating in the field within designated geofenced
areas.

The objectives of this project are to research, design, and implement a set of models and algorithms, together with an end -to-end data processing pipeline, to construct and maintain HD maps from crowd -sourced vehicle data. The framework will focus on:
1. Optimizing lane line extraction models based on GNSS telemetry data from fleets of vehicles.
2. Creating an end -to- end data processing pipeline from raw vehicle logs through map product generation.
3. Developing models and algorithms that leverage camera and perception semantics data to construct and refine lane -level HD maps and related map elements.
4. Performing system integration and map validation using a combination of simulation platforms and real -world in - vehicle tests.
5. Processing experiment data and creating technical documentation , including design documents, experiment reports, and integration guides.

The developed technologies will be used to support GM’s autonomous driving technology development to improve robustness, coverage, freshness, and customer experience.

Masters Degree in related engineering field/Computer ccience/Compter Engineering, PHD Preferred

3-5 years experience in ADAS Mapping, can include project, internships, relevant research

If interested, forward resume to tina.johnsonkelley@akkodisgroup.com or click Apply.

Pay Details: $40.00 to $52.00 per hour

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.

Equal Opportunity Employer/Veterans/Disabled

Military connected talent encouraged to apply

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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

Massachusetts Candidates Only: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.