IntraEdge
IntraEdge is hiring an AI Data Engineer.
Location: Detroit metro – must be local.
Employment type: Full-time.
Responsibilities
Build AI‑ready data pipelines: design, construct, and optimize scalable ETL and ELT pipelines 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 guarantee 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 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 resolve 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 transformation tasks. Qualifications
Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field. Experience: proven experience in data engineering or a similar role, with specific experience supporting AI and ML projects. Programming: fluency in Python and SQL; familiarity with Java or Scala is a plus. Frameworks: hands‑on experience with TensorFlow, PyTorch, Scikit‑learn, and LLM‑specific tools like LangChain or LlamaIndex. Big data: experience with Apache Spark, Hadoop, and distributed processing. Cloud platforms: proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data services. Databases: expertise in relational (SQL) and NoSQL databases, including vector databases for GenAI applications. DevOps and MLOps: experience with CI/CD, Docker, and MLOps tools like MLflow. Seniority level
Mid‑Senior level Employment type
Full‑time Job function
Information Technology Industries
IT Services and IT Consulting Referrals increase your chances of interviewing at IntraEdge by 2x. Detroit, MI $112,597.33‑$152,810.66 1 month ago
#J-18808-Ljbffr
Build AI‑ready data pipelines: design, construct, and optimize scalable ETL and ELT pipelines 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 guarantee 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 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 resolve 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 transformation tasks. Qualifications
Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field. Experience: proven experience in data engineering or a similar role, with specific experience supporting AI and ML projects. Programming: fluency in Python and SQL; familiarity with Java or Scala is a plus. Frameworks: hands‑on experience with TensorFlow, PyTorch, Scikit‑learn, and LLM‑specific tools like LangChain or LlamaIndex. Big data: experience with Apache Spark, Hadoop, and distributed processing. Cloud platforms: proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data services. Databases: expertise in relational (SQL) and NoSQL databases, including vector databases for GenAI applications. DevOps and MLOps: experience with CI/CD, Docker, and MLOps tools like MLflow. Seniority level
Mid‑Senior level Employment type
Full‑time Job function
Information Technology Industries
IT Services and IT Consulting Referrals increase your chances of interviewing at IntraEdge by 2x. Detroit, MI $112,597.33‑$152,810.66 1 month ago
#J-18808-Ljbffr