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AI​/Machine Learning Engineer; MLLM - Automotive industry

Job in Detroit, Wayne County, Michigan, 48228, USA
Listing for: Akkodis
Full Time position
Listed on 2026-04-20
Job specializations:
  • Engineering
    AI Engineer (Applied/Software)
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 115000 USD Yearly USD 115000.00 YEAR
Job Description & How to Apply Below
Position: AI/Machine Learning Engineer (MLLM) - Automotive industry

Do you possess a PhD with strong evidence of independent research, publication-quality work, and track record of publications at top machine learning and mobile/IoT systems venues?

If so, we are interested in speaking to you!

Due to recent team expansion, Akkodis is seeking a full-time AI/Machine Learning Engineer to join our dedicated team in the Detroit Metropolitan area for the next several years exclusively supporting the automotive industry. In this role, you'll design and implement end-to-end machine learning system prototypes in Python, with an emphasis on robust, well-structured, and reproducible code while contributing to multimodal large language model (MLLM) experimentation and prototyping, focusing on camera, audio, and text signals for connected applications.

Starting Salary Range:
Up to $115,000 (rate commensurate based on experience and education levels).

AI/Machine Learning Engineer job responsibilities include:
  • Contribute to multimodal large language model (MLLM) experimentation and prototyping, focusing on camera, audio, and text signals for connected applications.
  • Design and implement end-to-end machine learning system prototypes in Python, with emphasis on robust, well-structured, and reproducible code.
  • Model fine tuning and prompting experience for at least one major modality (e.g., text, camera, or audio); sensor fusion experience in multiple modalities is strongly preferred.
  • Integrate ML components in embedded systems and IoT platforms where applicable (experience in ML model compression and knowledge distillation strongly preferred).
  • Translate ideas into end-to-end pipelines, from data processing and model training to evaluation and deployment-ready artifacts.
  • Work with real-world data sets, including data collection, curation, labeling strategies, and model robustness analysis.
  • Explore and benchmark state-of-the-art ML methods, documenting findings and proposing improvements.
  • Communicate results through clear technical reports, presentations, and code documentation.
Required Qualifications:
  • Hold an advanced degree (PhD) in a relevant field (e.g., Electrical/Computer Engineering, Computer Science, or related), with strong evidence of independent research, publication-quality work, and a track record of publications at top machine learning and mobile/IoT systems venues (e.g., CVPR, NeurIPS, ICML, ICLR, Mobi Sys, INFOCOM, Sen Sys) is strongly preferred.

If you are interested in the AI/Machine Learning Engineer role, please click EASY APPLY. For other opportunities available at Akkodis go to

Equal Opportunity Employer/Veterans/Disabled

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

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

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