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Machine Learning Engineer Two Jobs in Detroit, MI

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Senior Machine Learning Engineer

Detroit, MI · Remote

$126K - $180K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you'll contribute to the development of cutting-edge AI solutions to combat ...

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you'll contribute to the development of cutting-edge AI solutions to combat ...

Staff Machine Learning Engineer - Mapping

Warren, MI · On-site

$185K - $335K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Role We are looking for a Staff Machine Learning Engineer to serve as a technical leader for automated map reconstruction within our Mapping Engineering team. In this role, you will architect and ...

In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the following skills and experience. Essential * Extensive and proven track record of shipping deep ...

Showing results 21-40

Machine Learning Engineer Two information

See Detroit, MI salary details

$31.2K

$127.5K

$191.6K

How much do machine learning engineer two jobs pay per year?

As of Aug 18, 2026, the average yearly pay for machine learning engineer two in Detroit, MI is $127,477.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $153,400.00 per year, depending on experience, location, and employer.

Are machine learning engineers still in demand?

Yes, machine learning engineers are in high demand across various industries due to the increasing adoption of AI and data-driven solutions. They are sought after for their skills in algorithms, programming, and tools like Python and TensorFlow, with job growth expected to continue as AI applications expand.

What are popular job titles related to Machine Learning Engineer Two jobs in Detroit, MI?

For Machine Learning Engineer Two jobs in Detroit, MI, the most frequently searched job titles are:

What cities near Detroit, MI are hiring for Machine Learning Engineer Two jobs?

Cities near Detroit, MI with the most Machine Learning Engineer Two job openings:

Machine Learning Engineer

Bespoke Labs

Warren, MI • On-site

Full-time

Re-posted yesterday


Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination