ZipRecruiter

Log In

1

Machine Learning Engineer Jobs in Rochester Hills, MI

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 ...

Varsity Tutors

Machine Learning Tutor

Detroit, MI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Rochester Hills, MI

Machine Learning Engineer information

See Rochester Hills, MI salary details

$29K

$118.5K

$178.1K

How much do machine learning engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning engineer in Rochester Hills, MI is $118,526.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,400.00 and $142,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What cities near Rochester Hills, MI are hiring for Machine Learning Engineer jobs? Cities near Rochester Hills, MI with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Rochester Hills, MI as of July 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $118,526 per year, or $57 per hour.
Principal Machine Learning

Principal Machine Learning

AAA Life Insurance Company

Livonia, MI • On-site, Remote

Full-time

Re-posted 3 days ago

Job description

Overview
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.
Responsibilities
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

Qualifications
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.
#LI-Remote

Apply