Senior MLOps Engineer: Real-Time ML Platform

Sigma Software; Województwo małopolskie; On-site; PLN 200,000 - 320,000; Full time

Job summary

Sigma Software is seeking a Senior MLOps Engineer to build and maintain a production-grade ML platform within a large-scale AdTech ecosystem. You will own ML training orchestration, model lifecycle automation, and observability across multi-tenant environments.

The role emphasizes scalable pipelines, CI/CD for ML, and collaboration with DevOps to deliver reliable ML infrastructure. Strong Python, Kubernetes, Docker, and cloud expertise are required.

Qualifications

• 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.
• Hands‑on production experience with MLflow, Kubeflow, Airflow, Argo Workflows, Vertex Pipelines, or similar orchestration and ML lifecycle platforms.
• Experience with ML platforms and model lifecycle tools such as Vertex AI, MLflow, or Kubeflow.
• Strong understanding of ML observability including drift detection, train/serve skew monitoring, and incident response.
• Experience designing or supporting multi‑tenant ML systems and isolated model environments.
• Experience working with cloud platforms, preferably GCP.
• Experience with infrastructure‑as‑code tools such as Terraform.
• Experience with Linux environments.
• Understanding of the ML lifecycle and productionization processes.
• Upper‑Intermediate English level or higher.

Responsibilities

• Build and maintain ML training orchestration pipelines across hourly, daily, and weekly schedules.
• Implement retries, backfills, and idempotent execution mechanisms.
• Design and support model registry workflows including versioning, lineage, evaluation gates, and promotion processes.
• Develop isolated per‑advertiser model environments with namespace and configuration separation.
• Build scalable refresh pipelines and publishing workflows for serving infrastructure.
• Implement shadow mode and champion/challenger deployment strategies.
• Develop monitoring and alerting for ML‑specific metrics including feature drift, prediction drift, train/serve skew, and calibration decay.
• Ensure reproducibility of ML workflows 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.

Skills

Python

Kubernetes

Docker

Cloud platforms

CI/CD for ML

Model lifecycle automation

Observability

Multi-tenant architecture

English proficiency

Tools

Kubernetes

Docker

Vertex AI

Kubeflow

Airflow

Argo Workflows

Terraform

GCP

MLflow

Job description

Sigma Software is seeking a Senior MLOps Engineer to build and maintain a production-grade ML platform within a large-scale AdTech ecosystem. You will own ML training orchestration, model lifecycle automation, and observability across multi-tenant environments.

The role emphasizes scalable pipelines, CI/CD for ML, and collaboration with DevOps to deliver reliable ML infrastructure. Strong Python, Kubernetes, Docker, and cloud expertise are required.