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Open nowPosted 178 days ago

MLOps Engineer

antalpl1,060 open roles

Where
Warszawa
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Your applicationOpen nowMLOps Engineerantalpl · Warszawa

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on antalpl's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market. antalpl postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 178 days ago

antalpl median: 1 days open

The posting

MLOps Engineer (Junior/Mid)

📍 Warszawa – Rondo Daszyńskiego 🏡 Model hybrydowy (1 dzień w biurze / 4 dni zdalnie)

O roli

Do zespołu rozwijającego platformę AI w branży ubezpieczeniowej poszukujemy osoby na stanowisko MLOps Engineer, która chce rozwijać się w kierunku budowy i utrzymania środowisk ML w chmurze Azure.

Rola łączy elementy DevOps, Cloud i Machine Learning, ale z naciskiem na rozwój i naukę w praktyce — będziesz pracować blisko bardziej doświadczonych inżynierów i zespołów Data Science.

Zakres odpowiedzialności

  • Wsparcie w budowie i utrzymaniu środowiska MLOps w Azure (cloud + on-prem)
  • Udział w tworzeniu pipeline’ów CI/CD dla rozwiązań ML
  • Praca z Dockerem i Kubernetes (AKS) przy wdrażaniu modeli
  • Wsparcie monitoringu modeli (jakość, drift, logowanie, alerty)
  • Automatyzacja procesów związanych z trenowaniem i deploymentem modeli
  • Współpraca z zespołami Data Science i IT

Wymagania (must have)

  • ok. 2+ lata doświadczenia w DevOps / MLOps / Software Engineering
  • Podstawowa/praktyczna znajomość Docker i Kubernetes
  • Doświadczenie z chmurą (Azure / AWS / GCP)
  • Znajomość Python i podstaw skryptowania (Bash/Shell)
  • Pierwsze doświadczenia z pipeline’ami CI/CD (GitHub Actions / Jenkins / Azure DevOps)
  • Chęć rozwoju w obszarze MLOps i pracy z modelami ML

Nice to have

  • Pierwsze doświadczenia z MLflow / Kubeflow
  • Znajomość Terraform / IaC (nawet na poziomie podstawowym)
  • Kontakt z tematami LLM / GenAI / RAG
  • Narzędzia monitoringu (np. Grafana, Prometheus)

Kogo szukamy?

  • Osoby z podejściem „learning & automation mindset”
  • Kogoś, kto chce rozwijać się na styku ML i infrastruktury
  • Kogoś, kto nie boi się uczyć nowych technologii w praktyce
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