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Machine Learning Jobs in Detroit, MI (NOW HIRING)

Autodesk

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

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How much do machine learning jobs pay per year?

As of Jul 16, 2026, the average yearly pay for machine learning in Detroit, MI is $38,964.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,700.00 and $42,100.00 per year, depending on experience, location, and employer.

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-paying industries such as finance or technology, can earn salaries of $500,000 or more annually. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of impactful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data analysis, and programming with tools like Python and TensorFlow. Such roles usually demand extensive experience, a strong educational background, and sometimes leadership responsibilities in developing or deploying AI systems.

What is a Machine Learning job?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are some typical day-to-day responsibilities in a Machine Learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With machine learning skills, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These positions typically require knowledge of programming languages like Python or R, experience with machine learning frameworks, and strong analytical skills. They are found across industries including technology, finance, healthcare, and automotive sectors.

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

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

Which 3 jobs will survive AI?

Machine Learning roles such as data scientists, AI specialists, and machine learning engineers are expected to persist as AI advances, due to their need for complex problem-solving, domain expertise, and ongoing model development. These jobs require advanced skills in programming, statistics, and understanding of AI tools, making them less susceptible to automation. Continuous learning and staying updated with new algorithms and frameworks are essential for these positions.
What are the most commonly searched types of Machine Learning jobs in Detroit, MI? The most popular types of Machine Learning jobs in Detroit, MI are:
What are popular job titles related to Machine Learning jobs in Detroit, MI? For Machine Learning jobs in Detroit, MI, the most frequently searched job titles are:
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What cities near Detroit, MI are hiring for Machine Learning jobs? Cities near Detroit, MI with the most Machine Learning job openings:
Machine Learning jobs near you

Staff Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

$160K - $200K/yr

Full-time

Posted 6 days ago

Job description

About Mariana Minerals
Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We're reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.
The Role
Mariana Minerals is building the critical minerals supply chain from the ground up-and we're looking for a Staff Machine Learning Engineer to help make it autonomous.
We're not a software company selling tools to mining operators. We are a mining company that builds software. Mariana designs, builds, commissions, and operates our own mines and refineries. We develop proprietary chemical processes and run them at lab, pilot, and commercial scale. Today, we're producing battery-grade lithium salts from real oil and gas wastewater in our facilities. Our first commercial-scale lithium production facility, Lithium One, is targeting initial production in Q1 of 2027.
As a Staff Machine Learning Engineer at Mariana, you'll set the technical direction for how we make refining autonomous. You'll define how control models are built, validated, and trusted on live equipment across our circuits and facilities-and you'll personally take on the hardest modeling problems standing between us and fully autonomous operations. Your decisions will show up in real recovery rates, energy consumption, reagent usage, and uptime across every plant we run.
The Tech
This is some of the most interesting applied AI work happening today.
Our internal platform, uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots-but applied to autonomous, short-interval control of mineral refining circuits. Models adjust operating set points and configurations in real time, optimizing across lithium recovery, reagent consumption, energy intensity, and equipment uptime simultaneously.
The environment is noisy and non-stationary: wastewater compositions shift, ore grades change, equipment ages. The system must continuously adapt. The end goal is fully autonomous refining operations. When you ship here, you can literally watch the physics change.
Under the hood, that means training control models inside physically realistic simulators of our process units, then closing the gap against real plant data before anything touches live equipment.
What You'll Do
  • Own the autonomy roadmap across multiple circuits and facilities-deciding which unit operations to automate next and where investment in simulation and modeling pays off.
  • Define how control models are validated and certified safe to deploy on real refining equipment, including how the gap between simulation and reality is measured and closed.
  • Set the standards for our simulators and our modeling stack, so the whole team builds controllers that are reproducible, safe, and grounded in real project economics.
  • Personally solve the hardest modeling and control problems-non-stationarity, safety constraints, and multi-objective optimization across recovery, reagent use, energy, and uptime.
  • Partner with leadership on major capital and operational decisions, translating techno-economic and process insight into strategy.
  • Multiply the team through technical direction, design review, and mentoring of engineers at every level-and partner with our data engineering leaders to shape the data platform the autonomy roadmap requires. You own the modeling and the on-plant outcome; they own the backbone.
Desired Qualifications
  • 8+ years in machine learning engineering (or an exceptional 6+ with demonstrated org-level technical leadership), including production ML or control systems that ran in the real world.
  • A track record of setting technical direction for ML systems in physical, industrial, robotics, or control domains.
  • Deep expertise in reinforcement learning under non-stationarity, simulation and digital twins, and closing sim-to-real gaps-plus the judgment to know when a simpler approach wins.
  • Demonstrated ability to de-risk ambiguous, never-been-done problems: framing the objective, the success metric, and the path for others.
  • Strong cross-functional influence with both technical leadership and domain experts-chemists, metallurgists, process engineers, and geologists.
  • A builder at heart. Staff engineers here still ship.
Why This Role
We own the projects, generate the data, and close the loop. Every facility we build makes the software smarter-and the next facility faster and cheaper.
Mining is one of the last major industrial sectors that hasn't been rebuilt with modern software. The opportunity here isn't a feature gap-it's entire workflows and systems that don't exist yet.
Your work will directly shape how critical minerals are produced at scale in the coming decades. This is a role for someone who wants to set the technical direction of an entire industrial-AI platform while it's still being invented-not maintain one that already exists.
Our culture is built on three principles:
Extreme Ownership - We take full responsibility for outcomes, relentlessly driving toward solutions.
Engineer Out Requirements, then Automate - We simplify, optimize, and then automate for scale.
Share Your Legos - We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.
Join us as we build the future of responsible mineral sourcing and supply.

Apply