JobHabor

ML Ops Enigneer / 1

Inetum
Location
Warsaw, Masovian Voivodeship, Poland
Workplace
Employment
Full Time
Salary
Apply on the employer’s site

Posted 7mo ago

We are seeking an advanced ML Ops Engineer to design and implement the infrastructure required to host, orchestrate, and manage up to 1,500 ML scoring processes within a new Databricks environment. The focus of the role is on operationalizing the ML scoring pipelines by setting up a scalable, secure, and well‑monitored platform for data science teams to deploy their models.

Environment Configuration

  • Set up Databricks clusters, jobs, and workflows for large-scale ML scoring use cases.
  • Infrastructure as Code is used for reproducibility and governance (e.g., Terraform).
  • Implement scalable infrastructure capable of running thousands of ML scoring tasks.
  • Configure job scheduling, parallel execution strategies, and resource optimization.
  • Monitoring and alerting are integrated into the platform using cloud-native tools.
  • Security, compliance, and cost-efficiency are key pillars of the operational setup.

ML Ops Pipeline Integration

  • Develop deployment processes for ML models using Databricks MLflow or equivalent.
  • Implement version control and tracking for models, scoring code, and configuration files.

Execution Management

  • Build frameworks to orchestrate scoring of >1,500 ML models or scoring jobs.
  • Ensure resilience, fault tolerance, and restart capabilities for failed jobs.
  • Monitoring & Observability Integrate logging, alerting, and dashboards to monitor scoring throughput, latency, and failures.
  • Establish model performance monitoring hooks for post‑scoring analytics.

Automation

  • Work alongside Dev Ops Engineers to ensure common infrastructure and processes (e.g., shared storage, Delta Lake tables) serve both ML and BI use cases.
  • Automate provisioning of resources and deployments from CI/CD pipelines.
  • Utilize Infrastructure as Code (IaC) where feasible for reproducibility.

Collaboration

  • Work closely with data scientists, solution architects, and platform engineers to ensure smooth handover from model development to operational scoring.
  • Define operational SLAs for scoring workloads.

Work 3 times a week from an office in Warsaw, Lublin or Poznań.

We hereby inform you that Inetum Polska sp. z o.o. has implemented an internal reporting (whistleblowing) procedure. The content of the procedure and the possibility to submit an internal report are available at:

https://inetum.whispli.com/speakup?locale=pl

Skills

  • Machine Learning
  • Databricks
  • Terraform
  • MLflow
  • Delta Lake

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