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Remote Data Scientist Machine Learning Jobs in Detroit, MI

company826

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

... machine learning use cases. * Architect and deliver LLM-enabled Generative AI solutions (e.g ... Bachelor's degree required in Computer Science, Engineering, Data Science, or related field ...

Varsity Tutors

Linear Algebra Tutor

Ann Arbor, MI · Remote

$18 - $40/hr

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Linear Algebra Tutor

Detroit, MI · Remote

$18 - $40/hr

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Bright Vision Technologies

AI Security Engineer

Troy, MI · Remote

$105K/yr

AI Security Engineer - Remote Bright Vision Technologies is a technology consulting and software ... and machine learning systems. The role addresses the unique security challenges posed by LLMs ...

Aurora Patents

Software Patent Agent (Remote)

Ann Arbor, MI · Remote

$100K - $150K/yr

We are engineers and scientists first. What you'll do: You will help us navigate a dynamic growth ... machine learning, or related technical disciplines . Illustrative subject matter includes patent ...

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All JobsData Scientist Machine Learning JobsRemote Data Scientist Machine Learning JobsRemote Data Scientist Machine Learning Jobs in Detroit, MI

Remote Data Scientist Machine Learning information

See Detroit, MI salary details

$37.1K

$121.5K

$194.5K

How much do remote data scientist machine learning jobs pay per year?

As of Aug 15, 2026, the average yearly pay for remote data scientist machine learning in Detroit, MI is $121,507.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $134,600.00 per year, depending on experience, location, and employer.

What does a remote data scientist specializing in machine learning do?

A Remote Data Scientist specializing in Machine Learning uses advanced statistical techniques and programming skills to analyze large datasets and build predictive models, all while working from a remote location. They design, develop, and deploy machine learning algorithms to solve business problems, such as forecasting trends or automating processes. Their work often involves data cleaning, feature engineering, model selection, and collaborating with cross-functional teams to integrate these models into products or services. Remote data scientists typically use tools like Python, R, and cloud-based platforms to perform their tasks efficiently.

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

AspectRemote Data Scientist Machine LearningRemote Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; experience with ML frameworksSimilar educational background; may focus more on statistical analysis and data visualization
Work EnvironmentPrimarily involves developing ML models, coding in Python/R, and deploying algorithmsFocuses on data analysis, reporting, and insights generation, often with less emphasis on ML deployment
Employer & Industry UsageUsed in tech, finance, healthcare for predictive modeling and automationCommon across various industries for data analysis and business intelligence

While both roles require strong analytical skills and similar educational backgrounds, Remote Data Scientist Machine Learning specializes in developing and deploying machine learning models, whereas Remote Data Scientist focuses more on data analysis and reporting. The ML role often involves coding and algorithm development, making it more technical in nature.

How do remote data scientists specializing in machine learning typically collaborate with cross-functional teams?

Remote data scientists in machine learning often work closely with product managers, engineers, and business analysts through virtual meetings, collaborative platforms, and shared documentation tools. They regularly participate in sprint planning, code reviews, and brainstorming sessions to ensure alignment with project goals. Effective communication and proactive updates are essential for overcoming the challenges of remote collaboration and maintaining project momentum. Building strong relationships with team members across different time zones helps foster innovation and ensures that machine learning solutions are well-integrated into broader business objectives.

What are the key skills and qualifications needed to thrive as a remote data scientist specializing in machine learning?

To excel as a Remote Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, scikit-learn, PyTorch, and experience with cloud platforms like AWS or Azure are often required, along with relevant certifications. Strong problem-solving skills, effective communication, and the ability to work independently are crucial soft skills for remote collaboration and translating insights for diverse stakeholders. These competencies ensure the development of robust models, clear communication of findings, and successful project delivery in a distributed work environment.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Detroit, MI?

The most popular types of Data Scientist Machine Learning jobs in Detroit, MI are:

What are popular job titles related to Remote Data Scientist Machine Learning jobs in Detroit, MI?

For Remote Data Scientist Machine Learning jobs in Detroit, MI, the most frequently searched job titles are:

What job categories do people searching Remote Data Scientist Machine Learning jobs in Detroit, MI look for?

The top searched job categories for Remote Data Scientist Machine Learning jobs in Detroit, MI are:

What cities near Detroit, MI are hiring for Remote Data Scientist Machine Learning jobs?

Cities near Detroit, MI with the most Remote Data Scientist Machine Learning job openings:

Remote Data Scientist Machine Learning jobs near you
Infographic showing various Remote Data Scientist Machine Learning job openings in Detroit, MI as of August 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 25% In-person, and 75% Remote job distribution, with an average salary of $121,507 per year, or $58.4 per hour.

AI/ML and Data Engineer

company826

Southfield, MI • On-site, Remote

$104K - $125K/yr

Other

Re-posted 17 days ago

Job description

Description
Responsible for providing both strategic and hands-on technical leadership for SME's AI/ML, Generative AI, and modern data platforms, advancing SME's nonprofit mission to accelerate adoption of manufacturing technology and strengthen the manufacturing talent pipeline. The incumbent designs, builds, and deploys practical AI capabilities and governed data systems that enable SME insights, products, and services-including workforce development initiatives-while serving as an advisor under the direction of the Director to internal leaders, members, partners, and manufacturers.
A critical component of this role is end-to-end delivery: translating manufacturing-focused opportunities into secure, production-grade AI solutions (including traditional ML and LLM-enabled applications), building the underlying data foundation to support analytics and decision-making, and providing client-facing consulting services that demonstrate measurable value and responsible use of AI.
The position also contributes to organizational capability-building by coaching stakeholders on appropriate AI use, shaping standards-aligned governance practices, and representing SME's point of view on AI and data in manufacturing through partner engagement and industry thought leadership.
MAJOR FUNCTIONS:
  • Lead the design, development, and deployment of manufacturing-focused AI solutions, including predictive maintenance, anomaly detection, process optimization, and related applied machine learning use cases.
  • Architect and deliver LLM-enabled Generative AI solutions (e.g., Retrieval-Augmented Generation, tool use, and agentic workflows) that enable natural-language access to SME knowledge assets such as research content, standards-related material, membership and event data, and learning resources.
  • Build and maintain a modern, scalable data platform that ingests, curates, and governs structured and unstructured manufacturing-related datasets, ensuring data quality, metadata management, lineage, and appropriate access controls.
  • Design and implement database patterns (relational, lakehouse, and vector databases) to support analytics, AI development, and reliable retrieval across SME content and partner datasets.
  • Establish and mature MLOps/LLMOps practices, including CI/CD, model and prompt versioning, monitoring/observability, rollback procedures, and cost/performance optimization for production environments.
  • Define evaluation approaches and quality controls for AI systems, including performance metrics, monitoring for drift, and iterative improvement loops that maintain reliability and trust over time.
  • Oversee analytics engineering (ETL/ELT) supporting dashboards and reporting that inform SME decision-making on industry trends, program outcomes, member engagement, and organizational performance.
  • Conduct discovery workshops with manufacturers, members, and partners to identify priority AI/data opportunities, frame ROI and feasibility, and develop actionable implementation roadmaps.
  • Lead pilot and proof-of-value engagements from requirements through deployment and knowledge transfer, ensuring solutions are supportable, secure, and aligned with stakeholder needs.
  • Provide executive-level advisory services on AI adoption and data modernization, tailoring recommendations for both technical and non-technical stakeholders and enabling informed decision-making.
  • Author proposals, statements of work, technical approaches, and executive readouts that communicate scope, risks, outcomes, and measurable impact of AI/data initiatives.
  • Implement and champion AI/data governance and security practices aligned with relevant frameworks, including privacy safeguards, auditability, and responsible AI principles (bias mitigation, explainability, and safe use guidance).
  • Partner with internal stakeholders (e.g., workforce development, membership, research, standards-related groups, events, and marketing) to ensure AI/data initiatives align with SME priorities and deliver clear value to the manufacturing community.
  • Mentor team members and/or contractors in AI/data delivery best practices to improve consistency and execution quality.
  • Serve as an internal subject matter expert, enabling appropriate use of AI tools through guidance, enablement materials, and practical coaching.
  • Co-manage relationships with external technology partners, cloud providers, and vendors to ensure effective delivery, scalability, and cost discipline.
  • Represent SME at industry events and partner forums, providing thought leadership on AI and data in manufacturing and supporting SME's role as a trusted, industry-facing nonprofit.
  • Other duties as assigned.

Requirements
MINIMUM EDUCATION, SKILLS, AND EXPERIENCE REQUIREMENTS:
  • Bachelor's degree required in Computer Science, Engineering, Data Science, or related field; advanced degree preferred.
  • At least 8 years of progressive experience in AI/ML engineering, including a minimum of 3 years deploying traditional ML and Generative AI/LLM solutions into production.
  • Demonstrated track record building, shipping, and operating production AI systems using modern frameworks and best practices.
  • Extensive data engineering experience, including pipeline development, database design, and management of large-scale datasets.
  • Strong expertise with cloud platforms (AWS, Azure, or GCP) and associated data and AI services.
  • Demonstrated consulting and client-facing delivery experience, including workshop facilitation, requirements elicitation, and technical advisory execution.
  • Proven ability to lead cross-functional initiatives as a senior individual contributor and/or people leader, with strong collaboration skills across technical and business teams.
  • Exposure to manufacturing processes, systems, and operational challenges through industry experience or consulting engagements.
  • Working knowledge of data security, privacy, and governance practices; ability to implement controls appropriate for sensitive data and partner environments.
  • Excellent communication and presentation skills, with the ability to translate complex technical topics for varied audiences and senior stakeholders.

PREFERRED:
  • Experience with digital thread/digital twin concepts, manufacturing simulation, or related manufacturing systems integration.
  • Knowledge of manufacturing standards, technical publications, quality/reliability engineering, or certification/adherence environments.
  • Proficiency with platforms such as Snowflake, Databricks, Azure OpenAI, and/or AWS Bedrock.
  • Experience with compliance frameworks (e.g., SOC 2, NIST) and/or privacy regulations as applied to data and AI systems.
  • Advanced AI experience, including fine-tuning open-source LLMs for domain-specific manufacturing applications.
  • Familiarity with operational technology (OT) concepts and the realities of manufacturing data environments.
  • Experience developing AI solutions that incorporate manufacturing domain knowledge into model design, evaluation, and deployment approaches

KEY COMPETENCIES:
Core Competencies:
  • Communication and Collaboration
  • Relationship Management
  • Professionalism and Integrity
  • Critical Thinking and Decision-Making
  • Execution
  • Initiative, Leadership, and Development

Job Competencies:
  • AI Architecture and Solution Design
  • Data Architecture and Governance Implementation
  • AI Lifecycle and Model Operations Management
  • Responsible AI and Risk Mitigation
  • Technical Consulting and Stakeholder Advisory
  • External Partner and Vendor Collaboration

WORKING CONDITIONS:
  • Normal office environment
  • Regular, in-person attendance required
  • Primary office location: Southfield, MI
  • Travel required (up to 25%)

Apply