Hybrid MLOps Engineer

Posted 6 hours ago

Apply now

About the role

  • Machine Learning Software Engineer at Mobileye bridging machine learning research and robust production deployment. Developing scalable inference pipelines primarily in Python with infrastructure tools.

Responsibilities

  • Your role will include developing production deployment systems for classical and machine learning algorithms from research and building robust, scalable inference pipelines.
  • You will develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and developing new production capabilities.
  • Finally, you will need to learn and implement new deployment technologies and best practices that can address emerging production challenges as they arise, while staying current with the latest MLOps and inference optimization techniques.

Requirements

  • B.Sc. in Computer Science, Software Engineering, or related technical field.
  • 2+ years of experience developing and deploying production-grade software on cloud infrastructure, preferably for ML model deployment.
  • Strong problem-solving skills and ability to tackle complex, real-world production challenges.
  • Proficiency in Python and experience with containerization and orchestration technologies (Docker, Kubernetes)- advantage.
  • Hands-on experience with model serving frameworks and inference optimization- advantage.
  • Background in distributed systems- advantage.

Job title

MLOps Engineer

Job type

Experience level

JuniorMid level

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

Report this job

See something inaccurate? Let us know and we'll update the listing.

Report job