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Remote Ai Data Engineer Jobs in Detroit, MI (NOW HIRING)

company826

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

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 ...

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · Remote

$170K - $210K/yr

The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end ... data science teams and is open to fully remote candidates, with periodic travel expected for ...

Protera Health

Senior Data Engineer

Troy, MI · On-site +1

$100K - $136K/yr

You will champion the safe AI principles fundamental to our engineering culture. Key ... Fully remote work: work from your home or other private, secured area to help fit your lifestyle

Utilidata

Senior Software Engineer, DevOps

Ann Arbor, MI · On-site +1

$160K - $190K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... remote work. Our Commitments: Utilidata values the diversity of our team. We provide equal ...

Utilidata

Senior Software Engineer, DevOps

Ann Arbor, MI · Remote

$160K - $190K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... remote work. Our Commitments: Utilidata values the diversity of our team. We provide equal ...

Utilidata

VP, AI & Applications

Ann Arbor, MI · Remote

$230K - $290K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... The VP partners with the VP, Engineering on the platform that runs these methods in production, and ...

Mercor

Mechanical Engineer - AI Trainer

Detroit, MI · Remote

$70 - $110/hr

Remote Duration: 4-6 weeks Commitment: 20+ hours/week Role Responsibilities * Evaluate AI-generated ... Collaborate with AI research teams to enhance training data quality and downstream performance.

New

Kobie Marketing

AI Engineer

Detroit, MI · Remote

As a remote-first organization headquartered in St. Petersburg, Florida, Kobie values meaningful in ... Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex ...

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All JobsAi Data Engineer JobsRemote Ai Data Engineer JobsRemote Ai Data Engineer Jobs in Detroit, MI

Remote Ai Data Engineer information

See Detroit, MI salary details

$44.1K

$128.4K

$175.7K

How much do remote ai data engineer jobs pay per year?

As of Aug 24, 2026, the average yearly pay for remote ai data engineer in Detroit, MI is $128,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,400.00 and $136,100.00 per year, depending on experience, location, and employer.

What is a remote AI data engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

What are the key skills and qualifications needed to thrive as a remote AI data engineer?

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.

What are some common challenges faced by remote AI data engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What are popular job titles related to Remote Ai Data Engineer jobs in Detroit, MI?

For Remote Ai Data Engineer jobs in Detroit, MI, the most frequently searched job titles are:

What job categories do people searching Remote Ai Data Engineer jobs in Detroit, MI look for?

The top searched job categories for Remote Ai Data Engineer jobs in Detroit, MI are:

What cities near Detroit, MI are hiring for Remote Ai Data Engineer jobs?

Cities near Detroit, MI with the most Remote Ai Data Engineer job openings:

Remote Ai Data Engineer jobs near you

AI/ML and Data Engineer

company826

Southfield, MI • On-site, Remote

$104K - $125K/yr

Other

Re-posted 26 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