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Python Machine Learning Jobs in Michigan (NOW HIRING)

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 ...

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Python Machine Learning information

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$75

How much do python machine learning jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for python machine learning in Michigan is $51.09, according to ZipRecruiter salary data. Most workers in this role earn between $42.12 and $58.03 per hour, depending on experience, location, and employer.

What does a typical workday look like for a Python Machine Learning professional?

A typical workday for a Python Machine Learning professional often involves tasks like cleaning and pre-processing data, developing and training machine learning models, and evaluating their performance using statistical metrics. You'll collaborate with data engineers, data scientists, and product managers to understand business requirements and integrate models into production environments. Regularly, you'll participate in code reviews, team meetings, and troubleshooting sessions to optimize model performance and address any issues. This dynamic role requires both independent project work and frequent cross-functional collaboration to ensure that solutions meet real-world needs.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence or machine learning, often requiring advanced skills in programming, data analysis, and deep learning frameworks. Such roles are usually found in senior or executive levels, involving leadership, research, or specialized technical expertise, and may require relevant certifications or advanced degrees.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation may include base salary, bonuses, and stock options, especially in competitive markets.

Which 3 jobs will survive AI?

For Python machine learning professionals, roles such as data scientists, machine learning engineers, and AI researchers are likely to persist due to their need for complex problem-solving, domain expertise, and ongoing innovation. These jobs require advanced programming skills, understanding of algorithms, and the ability to adapt to new tools and techniques as AI evolves. Continuous learning and staying updated with frameworks like TensorFlow or PyTorch are essential for long-term relevance.

What is a Python Machine Learning job?

A Python Machine Learning job involves developing, training, and deploying machine learning models using Python. Professionals in this role work with libraries like TensorFlow, scikit-learn, and PyTorch to analyze data, build predictive models, and optimize algorithms. Responsibilities often include data preprocessing, feature engineering, model evaluation, and deploying models to production environments. These roles are commonly found in industries like finance, healthcare, and e-commerce, where data-driven decision-making is crucial.

What are the key skills and qualifications needed to thrive in the Python Machine Learning position, and why are they important?

To thrive as a Python Machine Learning professional, you need a strong background in statistics, programming (especially Python), data analysis, and machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Proficiency in libraries and frameworks like scikit-learn, TensorFlow, PyTorch, and familiarity with data visualization and version control tools are highly valued, as are relevant certifications such as TensorFlow Developer or AWS Machine Learning. Strong problem-solving ability, effective communication, and teamwork skills are important for collaboration and translating technical findings to non-technical stakeholders. These competencies enable you to design, develop, and deploy robust machine learning models that drive business solutions and innovation.

What is the salary of machine learning with Python?

The salary for a Python machine learning engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and industry. Professionals with strong skills in data analysis, deep learning, and relevant tools like TensorFlow or scikit-learn tend to earn higher salaries.
What are the most commonly searched types of Python Machine Learning jobs in Michigan? The most popular types of Python Machine Learning jobs in Michigan are:
Infographic showing various Python Machine Learning job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $106,276 per year, or $51.1 per hour.

Machine Learning Engineer

Bespoke Labs

Warren, MI โ€ข On-site

Full-time

Posted 22 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 โ€” 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 โ€” 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 โ€” SFT, RLHF, PPO, DPO, or reward model training โ€” 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 โ€” held-out sets, benchmark design, avoiding train/eval contamination