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Remote Advanced Ai Data Trainer Jobs in Michigan

company826

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

Advanced AI experience, including fine-tuning open-source LLMs for domain-specific manufacturing ... Data Architecture and Governance Implementation * AI Lifecycle and Model Operations Management

CSAA

In this highly strategic position, you will build and apply advanced simulation models to explore ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

micro1 AI

AI Trainer - Microbiology Expert

Detroit, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Lansing, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Warren, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

Corning

This is not a pure research or model-training role. We are looking for someone who is curious ... Data Science, or a related technical discipline. - 1-3 years of relevant experience in software ...

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Remote Advanced Ai Data Trainer information

What is a remote advanced AI data trainer?

A Remote Advanced AI Data Trainer is a professional who works remotely to create, label, and refine data used to train artificial intelligence (AI) models. They ensure the data is accurate and relevant, often working with complex datasets and advanced AI algorithms. Their tasks may include annotating text, images, or audio, as well as providing feedback to improve AI performance. This role requires strong attention to detail, familiarity with AI concepts, and the ability to work independently from any location.

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

To thrive as a Remote Advanced AI Data Trainer, you need strong analytical skills, a solid understanding of machine learning concepts, and a relevant degree or experience in data science or computer science. Familiarity with data annotation tools, AI training platforms, and programming languages like Python is often required. Excellent attention to detail, communication, and problem-solving abilities help set top performers apart in this role. These skills ensure high-quality data labeling and training, directly impacting the accuracy and effectiveness of AI systems.

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

Remote Advanced AI Data Trainers often encounter challenges such as maintaining clear communication with global teams, managing complex annotation guidelines, and ensuring data quality while working independently. To address these, it’s important to establish regular check-ins, use collaborative tools for feedback, and stay updated on best practices for data labeling. Proactively asking questions and participating in team discussions can also help ensure consistency and clarity in your work.

What is the difference between Remote Advanced Ai Data Trainer vs Remote AI Data Annotator?

AspectRemote Advanced Ai Data TrainerRemote AI Data Annotator
CredentialsTypically requires experience in AI, machine learning, or data science; certifications in data labeling or AI tools are commonOften requires basic data labeling skills; certifications are less common
Work EnvironmentRemote, collaborative with AI teams, involves training models and refining data setsRemote, focused on labeling and annotating data sets, often solo tasks
Industry UsageUsed in AI development, machine learning projects, and data science teamsUsed across industries for preparing training data for AI models

The Remote Advanced Ai Data Trainer and Remote AI Data Annotator roles both involve working with data for AI projects. However, the trainer typically requires more specialized knowledge, including AI concepts and model training experience, whereas the annotator focuses on labeling data. The trainer's role is more collaborative and involves refining AI models, while the annotator primarily performs data preparation tasks.

What are the most commonly searched types of Advanced Ai Data Trainer jobs in Michigan?

The most popular types of Advanced Ai Data Trainer jobs in Michigan are:

What are popular job titles related to Remote Advanced Ai Data Trainer jobs in Michigan?

For Remote Advanced Ai Data Trainer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Advanced Ai Data Trainer jobs in Michigan look for?

The top searched job categories for Remote Advanced Ai Data Trainer jobs in Michigan are:

What cities in Michigan are hiring for Remote Advanced Ai Data Trainer jobs?

Cities in Michigan with the most Remote Advanced Ai Data Trainer job openings:

Remote Advanced Ai Data Trainer jobs near you

AI/ML and Data Engineer

company826

Southfield, MI • On-site, Remote

$104K - $125K/yr

Other

Re-posted 24 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%)

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