Senior MLOps Engineer

Summary

Join GetInData | Part of Xebia, a leading data company, as an MLOps Engineer! While there isn't an immediate project, we are seeking candidates with exceptional skills to streamline machine learning project lifecycles. You will design and automate workflows, implement CI/CD pipelines, and ensure reproducibility and reliable experiment tracking. Collaboration with stakeholders and platform engineers is key to setting up infrastructure, automating model deployment, monitoring models, and scaling training. This role requires a wide range of technical skills in orchestration, storage, containerization, observability, and various ML algorithms. We offer competitive compensation, 100% remote work, flexible hours, and numerous professional development opportunities.

Requirements

• Proficiency in Python, as well as experience with scripting languages like Bash or PowerShell
• Knowledge of at least one orchestration and scheduling tool, for example, Airflow, Prefect, Dagster, etc
• Understanding of ML algorithms and distributed training, e.g., Spark / PyTorch / TensorFlow / Dask / Ray
• Experience with cloud services (Azure / AWS / GCP)
• Experience in frameworks such as Databricks
• Familiarity with tools like MLflow, W&B, and Neptune AI from the operations perspective
• Experience with containerization technologies like Docker and basic knowledge of container orchestration platforms like Kubernetes
• Understanding of continuous integration and continuous deployment (CI/CD) practices, as well as experience with related tools like GitHub Actions or GitLab CI

Responsibilities

• Collaborating with Platform Engineers to set the infrastructure required to run MLOps processes efficiently
• Implementing ML workflows / automating CI/CD pipelines
• Automating model deployment and implementing model monitoring
• Collaborating with Platform Engineers to implement backup and disaster recovery processes for ML workflows, especially models and experiments
• Collaborating with stakeholders to understand the key challenges and inefficiencies of Machine Learning project lifecycles within the company
• Keeping abreast of the latest trends and advancements in data engineering and machine learning

Benefits

• Salary: 160 - 200 PLN net + VAT/h B2B (depending on knowledge and experience)
• 100% remote work
• Flexible working hours
• Possibility to work from the office located in the heart of Warsaw
• Opportunity to learn and develop with the best Big Data experts
• International projects
• Possibility of conducting workshops and training
• Co-financing sport card
• Co-financing health care
• All equipment needed for work