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DevOps/MLOps Engineer with AI

Open 26d reposted 17× · 17 open copies

Hi there! If you’re looking for a high-impact position in an ambitious software house, we’ve got a match for you!

Currently, we are searching for a full-time MLOps/DevOps Engineer to cooperate with our US client - the company integrates production-grade, governed AI workflows into complex enterprise systems by addressing common friction points like poor integration and lack of domain expertise. The organization combines deep domain knowledge with cutting-edge capabilities to accelerate the deployment of reliable AI products.
Our client’s core mission is to make artificial intelligence work for complex enterprise workflows. Recognizing that most AI initiatives fail due to poor integration, gaps in domain specialization, a lack of governance, and unclear ownership-rather than flawed models—they focus on overcoming these exact friction points.
By combining decades of deep industry domain expertise with cutting-edge product AI capabilities, they accelerate production deployment and embed production-grade, governed AI workflows directly into some of the world’s most intricate enterprise systems. The leadership team consists of proven industry veterans with a track record of delivering groundbreaking AI products, backed by a board of senior executives with deep expertise in global consulting and software engineering.


⚠️ Due to the client's location, a daily standup around 5:00 – 6:00 PM Polish time, with required availability to work until at least 7:00 PM CET.

  • Minimum of 5+ years of hands-on experience in DevOps/MLOps
  • Being able to work until at least 7:00 PM CET
  • Proficiency with at least one cloud (preferably Azure or AWS)
  • Hands-on experience in self-hosting LLMs and building infrastructure for model evaluations
  • Solid knowledge of Kubernetes, Terraform, and Helm
  • Some experience with the open-source MLOps ecosystem,like model serving, model routing, vector databases/RAG, and experiment tracking tools (e.g. vLLM, LiteLLM, Qdrant, MLflow, Weights & Biases, or equivalent).

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