Senior MLOps Engineer (Python)

Quick Facts

• Role: Senior MLOps Engineer (Python)

• Focus: Production-ready classical ML (forecasting/time series) pipelines

• Work mode: Primarily remote; occasional on-site collaboration (~1x/month)

Description

You will deploy and maintain ML workflows across Azure cloud infrastructure and on-prem ETL clusters. You will collaborate with Data Scientists to build ML-driven forecasting solutions and refine internal engineering standards, with a focus on productionization and monitoring. The work targets classical ML (forecasting, time series, scikit-learn), not LLM/GenAI.

Responsibilities

• Develop reusable libraries, tools, and frameworks to standardize and accelerate end-to-end ML development and deployment

• Build and run training pipelines in AzureML and maintain cloud infrastructure using Infrastructure as Code (IaC)

• Use distributed processing (Spark) to parallelize computations on large datasets

• Diagnose and resolve technical issues while delivering high-availability, reusable, and adaptable engineering solutions

• Collaborate with engineering and data science teams to provide technical guidance and optimize core workflows

• Apply best practices for code quality, security, and scalability

Requirements

• Solid Python skills, including building production-grade libraries/tools

• Recent hands-on experience taking ML models to production, including deployment and monitoring

• Practical understanding of how Spark workloads scale (partitioning, performance tuning)

• Hands-on experience building CI/CD pipelines (GitHub Actions or Azure DevOps) and managing cloud infrastructure as code

• Cloud experience (Azure preferred; AWS/GCP also welcome) and Docker containerization

• Practical experience with orchestration tools such as Airflow

• Smooth cross-functional collaboration and involvement in technical design

• Clear and direct communication with tech and business partners; independent, pragmatic problem-solving

• English at a minimum B2/C1 level

• Primarily remote work with occasional on-site collaboration (~1x/month)

Benefits

• Flexible hybrid work model

• Home office reimbursement

• Language lessons

• Private healthcare

• Training package and in-house training

• MyBenefit points

• Ability to build a tech community (optional perks for B2B contractors)