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Machine Learning Defense Jobs in Michigan (NOW HIRING)

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

... defense technologies. We're reimagining the minerals supply chain by combining deep industry ... As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning ...

Eccalon LLC

AI Expert Robotics - onsite

Detroit, MI · On-site

Integrate machine learning and artificial intelligence models into robotic platforms and embedded ... Experience supporting government, defense, or regulated programs * Ability to obtain and maintain a ...

Deloitte

Manager - Data Science / Data Lake

Detroit, MI · On-site

... machine learning for cyber defense and operations. The team helps clients modernize security data environments, improve data operations, and apply scalable analytics and artificial intelligence ...

Torc Robotics

ML Engineer, I - App Engine

Ann Arbor, MI · On-site

They are seeking a Machine Learning Engineer to join their Application Engine Team, responsible for ... Torc provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense ...

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Machine Learning Defense information

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in deep learning, data science, and software engineering. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation packages.

How much does Lockheed Martin pay AI?

As a Machine Learning Defense professional at Lockheed Martin, salaries typically range from $80,000 to over $130,000 annually, depending on experience, education, and specific role. Compensation may also include benefits such as health insurance, retirement plans, and performance bonuses, with opportunities for career advancement in defense and aerospace sectors.

What are the key skills and qualifications needed to thrive as a Machine Learning Defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.

What jobs pay $2000 a day?

In the field of Machine Learning Defense, highly specialized roles such as senior machine learning engineers, AI security consultants, or cybersecurity analysts working on AI systems can command daily rates of around $2000 or more, especially with extensive experience, advanced certifications, and working on critical projects. These positions often require expertise in AI algorithms, cybersecurity, and relevant tools like Python, TensorFlow, or cybersecurity frameworks, and may involve consulting or contract work with flexible schedules.

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.

Which 3 jobs will survive AI?

In the field of Machine Learning Defense, roles such as cybersecurity analysts, AI security specialists, and data scientists are likely to persist as they require complex judgment, domain expertise, and ongoing adaptation to evolving threats. These jobs involve critical thinking, understanding of adversarial AI techniques, and specialized skills that are difficult to fully automate. Continuous learning and certifications in cybersecurity or AI are valuable for staying relevant in these roles.

What are some common challenges faced by professionals in Machine Learning Defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.
What are popular job titles related to Machine Learning Defense jobs in Michigan? For Machine Learning Defense jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in Michigan look for? The top searched job categories for Machine Learning Defense jobs in Michigan are:
What cities in Michigan are hiring for Machine Learning Defense jobs? Cities in Michigan with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

$120K - $160K/yr

Full-time

Posted 13 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 Machine Learning Engineers 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 Machine Learning Engineer at Mariana, you'll help build and improve the machine learning systems that control our mineral refining facilities. You'll start with well-scoped problems inside our simulators and training pipelines-and ramp quickly toward owning models that run on real, operating plants. Your work won't live behind dashboards or proxy metrics; you'll see its impact in real recovery rates, energy consumption, reagent usage, and uptime.
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
  • Run reinforcement learning experiments in our physically realistic simulators of mineral processing operations, and help turn the results into better controllers.
  • Build and refine pieces of our training environments-reward functions, observations, and action logic-with guidance from senior engineers.
  • Train control models, track and interpret their performance, and dig into why a model underperforms.
  • Help close the gap between simulation and reality by comparing model behavior against real plant data and flagging where the physics diverges.
  • Write clean, well-tested code and contribute to the services that put models into production.
  • Partner with process and chemistry experts to understand the unit operations you're modeling.
Desired Qualifications
  • 0-4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing-or a strong recent graduate with demonstrated project depth.
  • Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; exposure to reinforcement learning is a strong plus.
  • Proficiency in Python and comfort reading and debugging an existing codebase.
  • Curiosity about physical, industrial systems and eagerness to learn chemistry and process engineering from experts who will challenge your assumptions.
  • A self-starter who asks good questions, ships, and escalates blockers early.
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.
Why Join Us?
At Mariana Minerals, you'll be part of a mission-driven team reshaping the way critical minerals are sourced and supplied globally. You'll have the autonomy to make big decisions, the tool
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.
Mariana is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.

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