Senior ML Engineer

1 tydzień temu

Warszawa, Mazovia, Polska monday Pełny etat 90 000 zł - 120 000 zł rocznie

We are , a global software company transforming how businesses run. Our product suite can adapt to the needs of diverse industries and use cases within one powerful platform, empowering ~250,000 customers worldwide to reimagine how work gets done, drive greater efficiency, and scale like never before.

With over 2,900 employees across the globe, we grow by prioritizing transparency and knowledge sharing. We care about the impact you make, not the hours you clock, so we encourage initiative, ownership, and fresh thinking. We back our people with flexible work, wellness and mental health support, and a work environment built on collaboration.

About the role:

We're looking for an
ML Engineer - Infrastructure
to build the infrastructure that keeps our ML models
production-grade, cost-efficient, and reliable at scale
. You'll work on everything from observability and pipelines to disaster recovery, ensuring that our AI investments are always serving customers in real time.

We fully embrace the AI revolution and equip you with AI-powered IDEs, customizable agent rules, prompt engineering tools, and AI-infused CI/CD pipelines designed to boost speed and reliability. You'll also tap into AI-driven insights, helping you make smarter decisions, faster.

The role is based in our Warsaw office - established in 2022, it is a growing hub for engineers who love solving impactful problems. Teams here work on a broad range of challenges that push the boundaries of our products and infrastructure.

What you'll do:

  • Build and maintain a
    platform for model deployment
    integrated with standards (authentication and authorization, observability, disaster recovery).
  • Design and implement
    observability
    , cost projections, and
    release pipelines
    with automated testing, canary deployments, and rollback strategies.
  • Ensure ML models are
    reliable, scalable, and always production-ready
    .
  • Serve as on-call support for ML models,
    fixing issues and handling alerts
    .
  • Collaborate with AI engineers and data scientists to move research into
    production-grade services
    .
  • Lead
    future-facing efforts
    : fine-tuning models on data, balancing cost vs. performance, and optimizing GPU/CPU usage.
  • Drive continuous
    performance optimization -
    from tokenization pipelines to GPU parallelization strategies.

Your experience & skills:

  • 5+ years of experience as an
    ML/AI Engineer,
    MLOps, Infrastructure Engineer, or DevOps with ML focus
    .
  • Proven experience deploying and maintaining
    machine learning models in production at scale
    .
  • Strong knowledge of
    CI/CD pipelines, observability, testing, and rollback strategies
    .
  • Hands-on expertise with
    cloud infrastructure (AWS preferred)
    , GPUs, and containerized services.
  • Experience with
    cost monitoring and optimization
    for large-scale ML systems.
  • Comfort working with
    data scientists and ML engineers
    , translating research into robust services.
  • Bonus: Experience with
    fine-tuning models, managing training data, and balancing performance vs. cost trade-offs
    .

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