Senior MLOps Engineer

Hashlist; Auburn Hills (MI); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Hashlist is seeking a Senior MLOps Engineer to lead the AI and data analytics team in operationalizing machine learning and advancing MLOps maturity across the organization. The role is based in Auburn Hills, MI, with a hybrid work model and full-time commitment.

Responsibilities include building MLOps frameworks, deploying cloud-based ML services, implementing monitoring and automated retraining, and collaborating with the data platform team to ensure scalable, secure pipelines and timely

Qualifications

• MSc/MEng in STEM fields.
• 5+ years of professional coding experience in Python.
• 2+ years operationalizing data science projects (MLOps) with Databricks and MLflow.
• 5+ years with a cloud/DevOps stack (e.g., AWS, Docker, Kubernetes).
• Hands-on experience with PySpark and SQL.
• Proven track record deploying data science prototypes into production and building scalable ML pipelines.
• Understanding distributed data systems and open source frameworks.
• Ability to influence non-technical peers and leadership, and to mentor less experienced colleagues.

Responsibilities

• Lead the team's approach to MLOps and drive an automated data science workflow.
• 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 data infrastructure.
• Partner with peers to ensure scalability, business continuity, and timely turnaround.

Skills

Python

MLOps

Databricks

MLflow

AWS

Docker

Kubernetes

PySpark

SQL

Production deployment

Education

MSc / MEng in Statistics, Computer Science, Automatic Control, Engineering, or related STEM

Tools

Databricks

MLflow

AWS

Docker

Kubernetes

PySpark

SQL

Job description

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.

• Location: Auburn Hills, USA
• Working model: Hybrid
• 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