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Remote Applied Scientist Machine Learning Jobs in Michigan

General Motors

Senior Machine Learning Engineer

Warren, MI · On-site +1

$222.91K - $227.20K/yr

Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics Engineering or a related field and Two (2) years of experience as a Software Engineer, Machine Learning ...

Autodesk

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103.70K - $134.60K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Bachelor's degree in Computer Science, Engineering, or equivalent experience * 7+ years of ...

THOMSON REUTERS

Lead Research Engineer

Ann Arbor, MI · On-site +1

$100.30K - $132.10K/yr

The science and engineering of AI are rapidly evolving. We are looking for a lead who drives ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

OneStream Software

AI Consultant

Birmingham, MI · Remote

$104K - $130K/yr

Remote, USA Employment Type: Full-Time Compensation: $104,000.00 - $130,000.00 (Range applies to US ... applied machine learning and analytics. * 1-3 years of software implementation consulting ...

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Remote Applied Scientist Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Applied Scientist in Machine Learning, and why are they important?

To thrive as a Remote Applied Scientist in Machine Learning, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree and experience in ML algorithm development. Familiarity with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and tools for data processing and cloud computing is essential. Exceptional problem-solving ability, communication, and self-motivation are key soft skills for collaborating remotely and driving projects forward. These skills ensure you can independently design, implement, and communicate impactful machine learning solutions in a distributed work environment.

What can I expect in terms of collaboration and communication when working as a Remote Applied Scientist in Machine Learning?

As a Remote Applied Scientist in Machine Learning, you will frequently collaborate with cross-functional teams, including data engineers, product managers, and software developers. Communication typically takes place via video calls, chat platforms, and shared documentation, so strong written and verbal communication skills are essential. You may participate in regular virtual stand-ups, sprint planning, and code reviews to align on project goals and share progress. Remote work environments emphasize proactive communication and self-management to ensure seamless teamwork and project delivery.

What does a Remote Applied Scientist in Machine Learning do?

A Remote Applied Scientist in Machine Learning develops and implements machine learning models to solve real-world problems, often from a location outside of a traditional office. Their work involves analyzing large datasets, designing algorithms, and collaborating with teams to deploy scalable solutions. They may also conduct experiments to improve model performance and stay up to date with the latest research in the field. Communication and documentation are important, as they often work with cross-functional teams remotely.
What are the most commonly searched types of Applied Scientist Machine Learning jobs in Michigan? The most popular types of Applied Scientist Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for Remote Applied Scientist Machine Learning jobs? Cities in Michigan with the most Remote Applied Scientist Machine Learning job openings:
Remote Applied Scientist Machine Learning jobs near you
Principal Machine Learning

Principal Machine Learning

AAA Life Insurance Company

Livonia, MI • On-site, Remote

Full-time

Posted 17 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.
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