Machine Learning Engineer

Stefanini North America and APAC; Dearborn (MI); On-site; USD 120,000 - 170,000; Full time

Job summary

Stefanini North America and APAC is seeking a Machine Learning Engineer to design, build, deploy, and scale production-ready ML systems, pipelines, and Knowledge Graph solutions. The role focuses on cloud-native infrastructure and GenAI/LLM integrations in a modern data stack.

The ideal candidate combines strong Python and Java software development with hands-on experience in GCP, Vertex AI, BigQuery, and graph technologies to deliver scalable AI solutions and maintain robust ML workflows in

Qualifications

• 7+ years of IT experience, 3+ years of software development.
• 2+ years of AI and Graph Engineering experience.
• Strong Python and Java development skills.
• Experience with GCP and cloud-native AI/data platforms.
• Hands-on experience with Vertex AI and BigQuery.
• Experience with Dataflow/Apache Beam, Pub/Sub, Cloud Run/GKE, and Cloud Storage.
• Experience with graph data modeling and querying, including GQL, Neo4j, Spanner Graph, or similar technologies.
• Experience building LLM/AI agent systems, RAG, grounding, and model integrations.
• Familiarity with MCP or similar agent tool protocols.
• Experience with MLOps, CI/CD, and production deployments.
• Experience with Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting.
• Experience with Terraform, IAM, security, and secrets management.
• Ability to work with data producers to model and validate enterprise data.

Responsibilities

• Design and develop innovative machine learning models and software algorithms to solve complex business problems.
• Build, maintain, and optimize scalable ML pipelines, architecture, and infrastructure.
• Train, retrain, deploy, and manage ML models in production environments.
• Automate ML model deployment and training using CI/CD/CT and MLOps practices.
• Develop solutions involving computer vision, object detection, classification, tracking, and other ML applications.
• Build and deploy Knowledge Graph solutions using cloud-native data pipelines.
• Design and maintain graph entities, relationships, and data models.
• Develop and operate MCP services that expose graph and event-store data to AI agents.
• Build LLM and agent-based solutions using tools such as RAG, grounding, and enterprise AI APIs.
• Develop monitoring, observability, dashboards, alerting, and tracing for AI/data systems.
• Partner with data engineers and application teams to onboard and validate enterprise data.
• Establish data contracts, schema validation, quality checks, governance, and data lineage.

Skills

Python development

Java development

GCP Vertex AI

Graph data modeling

MLOps

CI/CD

Tools

Neo4j

Spanner Graph

BigQuery

Dataflow/Apache Beam

Job description

We are seeking a Machine Learning Engineer to design, build, deploy, and scale complex machine learning and AI solutions. This role will focus on developing production-ready ML systems, scalable cloud infrastructure, machine learning pipelines, Knowledge Graph solutions, and GenAI/LLM applications. The ideal candidate will have strong software engineering skills in Python and Java, hands‑on experience with GCP and Vertex AI, and experience working with AI/ML, data pipelines, graph technologies, and MLOps.

Responsibilities

• Design and develop innovative machine learning models and software algorithms to solve complex business problems.
• Build, maintain, and optimize scalable ML pipelines, architecture, and infrastructure.
• Train, retrain, deploy, and manage ML models in production environments.
• Automate ML model deployment and training using CI/CD/CT and MLOps practices.
• Develop solutions involving computer vision, object detection, classification, tracking, and other ML applications.
• Build and deploy Knowledge Graph solutions using cloud-native data pipelines.
• Design and maintain graph entities, relationships, and data models.
• Develop and operate MCP services that expose graph and event‑store data to AI agents.
• Build LLM and agent-based solutions using tools such as RAG, grounding, and enterprise AI APIs.
• Develop monitoring, observability, dashboards, alerting, and tracing for AI/data systems.
• Partner with data engineers and application teams to onboard and validate enterprise data.
• Establish data contracts, schema validation, quality checks, governance, and data lineage.

Experience Required

• 7+ years of IT experience, 3+ years of software development experience.
• 2+ years of AI and Graph Engineering experience.
• Strong Python and Java development skills.
• Experience with GCP and cloud-native AI/data platforms.
• Hands‑on experience with Vertex AI and BigQuery.
• Experience with Dataflow/Apache Beam, Pub/Sub, Cloud Run/GKE, and Cloud Storage.
• Experience with graph data modeling and querying, including GQL, Neo4j, Spanner Graph, or similar technologies.
• Experience building LLM/AI agent systems, RAG, grounding, and model integrations.
• Familiarity with MCP or similar agent tool protocols.
• Experience with MLOps, CI/CD, and production deployments.
• Experience with Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting.
• Experience with Terraform, IAM, security, and secrets management.
• Ability to work with data producers to model and validate enterprise data.

Experience Preferred

• Dataplex or Data Catalog.
• Streaming/CDC and event-driven architectures.
• Event-sourced data modeling.
• User-facing applications and dashboards using Knowledge Graph data.
• Experience with product development, manufacturing, quality, or supply-chain data.
• Data quality frameworks and schema evolution.