Senior MLOps Engineer
Istanbul, Turkey
Data Science, Python

At Zoolatech, we're dedicated to transforming the business landscape with our comprehensive expertise in software development. Collaboration with our client, a top-notch supplier of manufacturing, quality and compliance cloud-based life sciences software, is geared towards bringing life sciences products faster to market, so that those who need them can benefit from the newest advancements in life sciences industry.

Our client is building next generation data platform that will leverage AI/ML. We are looking for an ML Ops engineer who will build, maintain and enhance ML pipelines as well as develop a robust and scalable development environment for our ML team.

  • Become an integral part of ML team (MLOps engineers are working as one team with ML engineers)

  • Build, maintain and enhance ML pipelines

  • Build, maintain and enhance ML team development environment

  • 5-7 years experience in DevOps/DataOps/Platform Engineering/ML Ops

  • You have a strong background in software development and apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.

  • You have built MLOps pipelines before and have experience with Docker, EKS, Terraform, GitHub Actions and ArgoCD

  • You understand the tools and frameworks used by data scientists (e.g. notebooks, data analytics libraries, ML libraries, …)

  • Phyton or Java

  • You have excellent interpersonal, collaboration, and team skills

  • You are passionate about creatively solving business problems and can effectively prioritize and execute tasks in a high-pressure environment

  • You are successful in meeting multiple, challenging deadlines while communicating expectations clearly

You’ll be a stronger candidate if you have:

  • Experience building developer platform for ML engineers

  • Experience with Amazon’s Sage Maker or other cloud AI platforms and MLOps frameworks

  • Experience building tooling for configuration perf/tracking for fine tuning and model parallelism

  • Experience with cost captures and optimizations

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