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Executive Full Stack Machine Learning Engineer Jobs in Michigan

Bespoke Labs

Machine Learning Engineer

Warren, MI · On-site

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 ...

Max AI, Inc.

Full-Stack Engineer

Birmingham, MI · On-site

$140K - $220K/yr

Full Stack Engineer Responsibilities * Taking ownership of the entire product lifecycle-from ... A dedication to continuous learning and personal development. * A positive, collaborative spirit ...

Max AI, Inc.

Full-Stack Engineer

Birmingham, MI

$140K - $220K/yr

Full Stack Engineer Responsibilities * Taking ownership of the entire product lifecycle-from ... A dedication to continuous learning and personal development. * A positive, collaborative spirit ...

Max AI, Inc.

Full-Stack Engineer

Ann Arbor, MI · On-site

$140K - $220K/yr

Full Stack Engineer Responsibilities * Taking ownership of the entire product lifecycle-from ... A dedication to continuous learning and personal development. * A positive, collaborative spirit ...

Max AI, Inc.

Full-Stack Engineer

Ann Arbor, MI

$140K - $220K/yr

Full Stack Engineer Responsibilities * Taking ownership of the entire product lifecycle-from ... A dedication to continuous learning and personal development. * A positive, collaborative spirit ...

Max AI, Inc.

Full-Stack Engineer

Birmingham, MI · On-site

$140K - $220K/yr

Full Stack Engineer Responsibilities * Taking ownership of the entire product lifecycle-from ... A dedication to continuous learning and personal development. * A positive, collaborative spirit ...

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Executive Full Stack Machine Learning Engineer information

Will AI replace full-stack dev?

As an Executive Full Stack Machine Learning Engineer, it is unlikely that AI will fully replace full-stack developers, as their roles require complex problem-solving, creativity, and understanding of business needs that AI cannot replicate. AI tools can automate certain coding tasks and improve efficiency, but human oversight and expertise remain essential for designing, integrating, and maintaining full-stack applications. The evolving landscape emphasizes collaboration between AI and developers rather than replacement.

What engineer makes $500,000 a year?

An executive full stack machine learning engineer can earn $500,000 or more annually, especially with extensive experience, advanced skills in AI and software development, and working at large tech companies or startups with competitive compensation packages. High salaries often include base pay, bonuses, and stock options, reflecting seniority and expertise in the field.

Will MLE be replaced by AI?

An Executive Full Stack Machine Learning Engineer designs and implements AI systems, but AI is a tool that complements rather than replaces such roles. While automation and AI advancements can handle certain tasks, skilled engineers are needed for developing, maintaining, and improving complex machine learning solutions. Continuous learning and expertise in programming, data analysis, and model deployment remain essential in this field.

What is the salary of full-stack machine learning engineer?

The salary of a full-stack machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those requiring specialized skills in deep learning or cloud platforms may offer higher compensation.

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Michigan? The most popular types of Full Stack Machine Learning Engineer jobs in Michigan are:
What are popular job titles related to Executive Full Stack Machine Learning Engineer jobs in Michigan? For Executive Full Stack Machine Learning Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Executive Full Stack Machine Learning Engineer jobs in Michigan look for? The top searched job categories for Executive Full Stack Machine Learning Engineer jobs in Michigan are:
What cities in Michigan are hiring for Executive Full Stack Machine Learning Engineer jobs? Cities in Michigan with the most Executive Full Stack Machine Learning Engineer job openings:
Executive Full Stack Machine Learning Engineer jobs near you

Machine Learning Engineer

Bespoke Labs

Warren, MI • On-site

Full-time

Posted 21 days ago

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

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