Senior MLOps Engineer

We are looking for a Senior MLOps Engineer . This role sits within the AI and data analytics team of a major automotive player, leading how the team operationalizes machine learning and raising MLOps maturity across the organization.

Engagement details:

• Location: Auburn Hills, USA
• Working model: Hybrid
• Start date: ASAP
• Employment type: Full-time, Contract or Freelance

Responsibilities:

• Lead the team's approach to MLOps and drive a modern, agile, and automated approach to data science
• Develop, research, and implement MLOps frameworks, tools, and platforms for data science projects
• Design and implement infrastructure for machine learning cloud services
• Build microservices for task-specific AI cloud services
• Implement model performance monitoring and alerting
• Automate model retraining, monitoring, and versioning while improving code quality, security, and delivery speed
• Collaborate with the data platform team to create a feedback loop and improve the underlying data infrastructure
• Partner with peers to ensure scalability, business continuity, and appropriate turnaround time
• Own a backlog of activities to raise MLOps maturity and evolve the framework as new technologies emerge

Qualifications:

• MSc / MEng in Statistics, Computer Science, Automatic Control, Engineering, or a related STEM discipline
• 5+ years of professional coding experience in Python or other languages
• 2+ years operationalizing data science projects (MLOps) with Databricks and MLflow
• 5+ years with a cloud/DevOps stack (e.g., AWS, Docker, Kubernetes) and the ability to design complex architecture
• Hands-on experience with PySpark and SQL
• Proven track record converting data science prototypes into production and building scalable ML pipelines and services
• Understanding of distributed data systems and open source frameworks
• Ability to influence non-technical peers and leadership, and to mentor less experienced colleagues

Nice to have:

• CI/CD/CT pipeline implementation, front-/backend development (Django, Node.js, Streamlit), shell scripting and networking, broad data science and statistics background

Next steps:

• Press "Apply"
• We will review your application
• If qualified, you will be accepted into the network and can be considered for this and similar positions & projects