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Scale Ai Data Labeling Jobs (Flexible Options) in Michigan

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently. * Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and ...

Saransh Inc

Senior Robotics Data Engineer - Only W2

Warren, MI · On-site

$99K - $135K/yr

... AI. · Familiarity with robotics simulation platforms (e.g., Isaac Sim) and synthetic data generation. · Experience with data labeling tools and annotation workflows at scale. · Hands-on knowledge ...

ALTEN Technology USA

Practice Manager - AI & Data

Troy, MI · On-site

$160K - $190K/yr

Lead and manage the AI & Data practice * Manage and steer the allocation of practice resources ... Proven experience building and scaling technical teams or practices * Experience in: * Generative ...

Stellantis

Senior Data Engineer

Auburn Hills, MI · On-site

$100K - $136K/yr

This role helps engage business, engineering and ICT stakeholders around practical data needs and constraints, scale AI delivery through stronger data models, pipelines, integration pathways, quality ...

Deloitte

Agentic AI, AI & Data Science Engineer

Detroit, MI

$113K - $136K/yr

We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively. Qualifications Required: * 4+ years of experience delivering AI ...

DexKo Global

Head of AI Acceleration

Novi, MI

Central AI / Data / Technology teams * Functional leaders (Operations, Finance, Purchasing, etc ... Measurable business value delivered at increasing scale * AI becomes embedded in how work is done ...

Deloitte

Databricks Data Engineer II

Detroit, MI · On-site

$113K - $136K/yr

Join Deloitte's Core AI & Data practice and help organizations modernize data platforms, strengthen enterprise data foundations, and scale analytics and artificial intelligence capabilities. As a ...

Stellantis

Senior Data Engineer

Auburn Hills, MI

$100K - $136K/yr

This role helps engage business, engineering and ICT stakeholders around practical data needs and constraints, scale AI delivery through stronger data models, pipelines, integration pathways, quality ...

Deloitte

Sr Databricks Data Engineer

Detroit, MI

$113K - $136K/yr

As a Databricks Engineer in our AI & Data practice, you will design, build, and optimize cloud-based data engineering solutions that support large-scale transformation. You will work with business ...

General Motors

AI/ML Senior Researcher

Warren, MI · On-site

$92K - $117K/yr

Build, validate, deploy, and scale AI/ML models for high-impact manufacturing engineering, research ... Serve as a technical authority on model development, deployment architectures, data strategy ...

General Motors

AI/ML Senior Researcher

Warren, MI · On-site

$92K - $117K/yr

Build, validate, deploy, and scale AI/ML models for high-impact manufacturing engineering, research ... Serve as a technical authority on model development, deployment architectures, data strategy ...

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AI Data Engineer

AI Data Engineer

IntraEdge

Detroit, MI

$113K - $136K/yr

Full-time

Posted 16 days ago

Job description

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued.

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued. 
Education:Employment Type: FULL_TIME
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About IntraEdge

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At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

Social media

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