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Senior ML Engineer

  • Remote
    • Krakow, Podlaskie, Poland
    • Krosno, Dolnośląskie, Poland
    • Lublin, Lubelskie, Poland
    • Poland, Mazowieckie, Poland
    • Poznan, Wielkopolskie, Poland
    • Warsaw, Warmińsko-Mazurskie, Poland
    • Bucuresti, București, Romania
    • Sofia, Sofia, Bulgaria
    • Budapest, Budapest, Hungary
    • Miskolc, Borsod-Abaúj-Zemplén, Hungary
    • Porto, Lisboa, Portugal
    • Lisbon, Lisboa, Portugal
    • Athens, Attikí, Greece
    • Crete, Kríti, Greece
    • Riga, Rīga, Latvia
    • Vilnius, Vilniaus apskritis, Lithuania
    • Pilsen, Plzeňský kraj, Czechia
    • Praha, Praha, Hlavní město, Czechia
    • Bratislava, Bratislavský kraj, Slovakia
    • Ljubljana, Ljubljana, Slovenia
    • Ljubljana, Ljubljana, Slovenia
    +20 more
  • Engineering

-fully remote
-only for candidates based in EU
-b2b contract

Job description

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Senior ML Engineer to join one of our clients' team. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.

Responsibilities:

  • Build, maintain, and optimize end-to-end MLOps pipelines for machine learning workflows.

  • Deploy, monitor, and scale machine learning models in production environments.

  • Implement CI/CD pipelines for ML workflows and model lifecycle management.

  • Manage and optimize ML infrastructure using Docker, Kubernetes, and cloud platforms.

  • Collaborate closely with Data Scientists and Engineering teams to productionize ML models.

  • Ensure reliability, monitoring, and performance of ML systems in production.

  • Maintain best practices for model versioning, experiment tracking, and reproducibility.

Job requirements

Must-Have:

  • Senior-level experience in Machine Learning / MLOps engineering

  • Strong programming skills in Python

  • Hands-on experience with ML frameworks such as:

    • TensorFlow

    • PyTorch

    • scikit-learn

  • Experience with MLOps platforms/tools such as:

    • MLflow

    • Kubeflow

    • TFX or similar

  • Experience implementing CI/CD pipelines using tools such as:

    • Jenkins

    • GitLab CI

    • CircleCI

  • Strong experience with containerization and orchestration:

    • Docker

    • Kubernetes

  • Experience deploying and managing ML solutions on cloud platforms (AWS, GCP, or Azure)

Nice to Have:

  • Experience with big data technologies such as:

    • Apache Spark

    • Hadoop

    • Kafka

  • Experience with data visualization tools:

    • Tableau

    • Power BI

or