Senior MLOps Engineer (Python)

Quick Facts

• Role: Senior MLOps Engineer (Python)

• Focus: Production-ready machine learning pipelines for forecasting

• Work style: Primarily remote; occasional on-site collaboration (~monthly)

Description

Build and maintain ML workflows across Azure cloud and on-prem ETL clusters, collaborating with Data Scientists to deliver forecasting and time-series solutions. The role emphasizes classical machine learning (forecasting, time series, scikit-learn) and strengthening internal engineering standards. You’ll also create reusable toolsets and ensure models are deployed reliably with monitoring.

Responsibilities

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

• Work in an Azure environment, including AzureML training code and Infrastructure as Code (IaC) for cloud infrastructure

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

• Diagnose and resolve technical issues to deliver high-availability, reusable, and adaptable solutions

• Collaborate with cross-functional engineering and data science teams to optimize core workflows

• Promote best practices in code quality, security, and scalability

• Make autonomous, data-driven technical decisions that support business growth

Requirements

• Advanced Python skills, including building production-grade libraries or tools used by other engineers

• Recent hands-on experience productionizing ML models, including deployment and monitoring

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

• Hands-on CI/CD experience using GitHub Actions or Azure DevOps

• Infrastructure as Code (IaC) experience

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

• Practical experience with orchestration tools such as Airflow

• Clear communication with technical and business partners

• High independence and pragmatic problem-solving

• English at B2/C1 level

• Primarily remote work with occasional on-site collaboration (~once a month)

Benefits

• Flexible hybrid work model

• Home office reimbursement

• Language lessons

• Private healthcare

• Training package and in-house training (Virtusity)

• MyBenefit points

Access to the perks is optional and voluntary for B2B contractors.