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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Machine Learning Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions that leverage Machine ...

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 ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Machine Learning information

See Michigan salary details

$22.2K

$37.1K

$76.7K

How much do machine learning jobs pay per year?

As of Jul 16, 2026, the average yearly pay for machine learning in Michigan is $37,116.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,300.00 and $40,100.00 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 Michigan? The most popular types of Machine Learning jobs in Michigan are:
What are popular job titles related to Machine Learning jobs in Michigan? For Machine Learning jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Machine Learning jobs? Cities in Michigan with the most Machine Learning job openings:
Principal Machine Learning

Full-time

Re-posted 5 days ago


Job description

General Purpose

At AAA Life, we are building a future-focused team using AI and automation to transform life insurance operations. If you're driven by meaningful work and want to deliver solutions that matter to millions of members, this is your opportunity.

We are seeking a Principal Machine Learning Engineer to serve as a technical leader within our Automation and AI organization. This role is accountable for defining and driving AI strategy, architecture, and delivery across multiple high-impact enterprise initiatives. The Principal MLE will lead the development of production-grade AI and agentic systems, ensuring successful deployment of business-critical solutions across Claims, Underwriting, and Member Services. These systems directly impact operational efficiency, decision quality, and customer experience at scale. This role requires deep expertise in modern AI, particularly in designing and deploying autonomous, agentic systems, an emerging and highly specialized area with a limited talent pool. This is a hands-on technical leadership role responsible for delivering enterprise-scale AI solutions where architectural decisions, system reliability, and model behavior have direct and measurable business impact.


Position Responsibilities

  • Establish engineering standards, best practices, and evaluation frameworks for AI systems
  • Lead technical decision-making for model selection, system design, and deployment strategies
  • Act as the subject matter expert for agentic AI and modern LLM-based systems within the organization
  • Architect and deliver production-grade, multi-step AI agents capable of autonomous reasoning, tool orchestration, task decomposition, memory management, and human-in-the-loop escalation—requiring specialized expertise in emerging agentic AI frameworks
  • Design and deliver AI systems on enterprise cloud platforms (e.g., AWS, Azure), including LLM services (AWS Bedrock, Azure OpenAI), supporting high-volume, business-critical workflows with strict requirements for reliability, auditability, and performance
  • Own the agent evaluation and observability stack, including benchmarking, tracing, regression testing, and performance monitoring
  • Optimize LLM inference costs and resource utilization for production workloads
  • Partner with business leaders to identify, prioritize, and shape AI-driven initiatives aligned with organizational goals
  • Translate complex business problems into scalable AI solutions with measurable impact
  • Drive roadmap planning and investment decisions related to AI and automation
  • Collaborate with IT, data engineering, and operations teams to integrate AI solutions into enterprise systems
  • Mentor and develop machine learning engineers and data scientists
  • Provide technical guidance and elevate team capabilities in modern AI practices
  • Ensure responsible and compliant use of AI systems, including managing risks related to model behavior, data usage, and regulatory considerations in a highly regulated industry
  • Lead evaluation and integration of external AI platforms and vendors, including assessment of cost, intellectual property, scalability, security, and long-term architectural impact

Core Competencies

  • Excellent communication skills and ability to explain ML results to non-technical audiences
  • Proven ability to operate with a high degree of autonomy and accountability
  • Experience driving adoption of AI solutions in enterprise environments
  • Ability to influence technical direction and investment decisions across organizational boundaries
  • Track record of building engineering culture and raising the technical bar within a team

Education/Experience

  • Master’s degree (or higher) in Computer Science, Engineering, Statistics, or related quantitative field
  • 10+ years of hands-on experience in machine learning, AI, or related disciplines
  • 2+ years of recent experience architecting and delivering LLM-based and agentic AI systems in production
  • Proven track record of delivering end-to-end AI solutions, from problem definition through production deployment
  • Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow)

Preferred Qualifications

  • Experience building agentic systems for document-heavy workflows (e.g., claims, underwriting, policy processing)
  • Experience with enterprise cloud AI platforms (AWS Bedrock, SageMaker, Azure OpenAI)
  • Experience with agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, or equivalent)
  • Experience with AI observability and evaluation tools (e.g., Langfuse, LangSmith, or similar)
  • Familiarity with Model Context Protocol (MCP) or equivalent tool-integration standards
  • Experience deploying AI systems in regulated environments (insurance, finance, healthcare)
  • Experience leading AI architecture across multiple teams or domains

 

Essential Job Functions

While performing the duties of this job, the employee is frequently required to stand, walk, sit, use hands to finger, handle, or feel and talk or hear.  Specific vision abilities required by this job include close vision, distance vision, color vision, depth perception, and ability to adjust focus.

This job requires the ability to perform duties contained in the job description for this position, including, but not limited to, the above requirements.  Reasonable accommodations will be made for otherwise qualified applicants as needed to enable them to fulfill these requirements.

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