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Senior MLOps / ML Platform Engineer

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Senior MLOps / ML Platform Engineer in Remote new

  • Sigma Software
  • Full time
  • Email
  • Poland

Responsibilities

  • Build and maintain scheduled ML training orchestration pipelines with retries, backfills, and idempotent execution.
  • Develop model registry, versioning, lineage, evaluation-gate, promotion, refresh, and publishing workflows.
  • Design isolated per-advertiser model environments and scalable multi-tenant ML infrastructure.
  • Implement shadow-mode and champion/challenger deployment strategies for serving systems.
  • Develop ML observability for feature drift, prediction drift, train/serve skew, calibration decay, and operational incidents.
  • Ensure reproducibility using containerized environments, pinned dependencies, and data snapshots.
  • Monitor training and scoring costs across tenants.
  • Collaborate with DevOps and SRE engineers on CI/CD and infrastructure automation.
  • Prepare operational documentation and platform handover materials.

Requirements

  • 5+ years of experience in MLOps, ML platform engineering, or infrastructure engineering supporting production ML systems.
  • Strong Python skills and experience building platform-level tooling and automation.
  • Hands-on experience with Kubernetes and Docker.
  • Experience building CI/CD pipelines for ML workloads.
  • Production experience with MLflow, Kubeflow, Airflow, Argo Workflows, Vertex Pipelines, or similar ML orchestration and lifecycle platforms.
  • Experience with cloud platforms, preferably GCP, and infrastructure-as-code tools such as Terraform.
  • Strong understanding of ML observability, drift detection, train/serve skew monitoring, incident response, and the ML production lifecycle.
  • Experience designing or supporting multi-tenant ML systems and isolated model environments.
  • Experience working with Linux environments.
  • Upper-Intermediate English level or higher.
  • Preferred experience with feature stores, feature consistency management, large-scale batch scoring, experiment tracking, evaluation gates, on-premises Kubernetes, bare-metal Linux, DVC, lakeFS, Bigtable, Redis, Aerospike, GPU scheduling, training cost optimization, and SOC 2, ISO 27001, or GDPR-related compliance.

Benefits

  • Opportunity to work on cutting-edge ML infrastructure for a large-scale AdTech ecosystem.
  • Collaboration with experienced engineers and influence over architecture decisions in a long-term strategic engagement.
  • The project is designed for long-term customer ownership and combines large-scale ML infrastructure, multi-tenant architecture, model lifecycle automation, and observability.

Sigma Software

Sigma Software delivers innovative software solutions that empower businesses to streamline operations, enhance customer experiences, and drive digital transformation. By combining agile development practices with deep industry expertise, we create scalable, secure, and user‑friendly applications...

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