Senior Machine Learning Engineer – ML Ops & Data Platform

About the role

We are seeking a Senior Machine Learning Engineer to design, build, and maintain scalable ML and data platforms for connected vehicle and agentic AI initiatives. The role focuses on cloud‑based pipelines, performance optimization, and secure, cost‑effective production on Google Cloud Platform, working onsite in Dearborn, MI.

Key responsibilities

• Build and scale ML data pipelines in GCP for large volumes of connected vehicle data.
• Optimize ML models for performance, security, reliability, and cost.
• Support continual learning and monitor data quality and model performance.
• Develop analytical data products using streaming (Kafka/GCP Pub/Sub) and batch ingestion.
• Maintain infrastructure with Terraform and design CI/CD pipelines for data and ML workloads.
• Implement and enforce enterprise data governance, lineage, and quality standards.
• Address code quality and security findings using tools such as SonarQube, Checkmarx, Fossa, and Cycode.
• Collaborate with data scientists, analytics stakeholders, and product teams in an Agile environment.

Required profile

• Senior‑level experience in ML Ops and data platform engineering.
• Strong technical communication and ability to work closely with cross‑functional stakeholders.
• Hands‑on experience delivering production ML solutions on GCP.

Required skills

• Machine Learning & ML Ops
• Google Cloud Platform (GCP)
• Python, SQL, Java
• Apache Kafka or GCP Pub/Sub
• Apache Spark
• REST APIs & microservices
• CI/CD, GitHub, Docker, Tekton
• Terraform
• SonarQube, Checkmarx, Fossa, Cycode
• TensorFlow (preferred)