MLOps Engineer

Quick Facts

• Role: MLOps Engineer

• Focus: End-to-end MLOps environment for predictive ML models in production (deployment, monitoring, lifecycle management)

Description

You will design, build, and develop an end-to-end MLOps environment that enables deploying predictive models to production, monitoring them, and managing the full lifecycle of Machine Learning models and decision engines.

You will create CI/CD and ML deployment automation following DevOps and MLOps best practices, evaluate cloud technologies, and implement processes on platforms such as Azure, Microsoft Fabric, and SAS Viya.

You will also integrate on-prem environments with the cloud and develop and monitor workflows across the full lifecycle of analytical models.

Responsibilities

• Design, build, and evolve MLOps environments supporting deployment, automation, and maintenance of ML models and decision engines

• Create and maintain CI/CD processes and automate ML solution deployments in line with DevOps/MLOps best practices

• Analyze new technologies and cloud services and recommend their use in ML/AI architecture

• Design and implement processes on cloud/analytics platforms such as Azure, Fabric, and SAS Viya

• Analyze platform development needs and design solutions integrating on-prem with the cloud

• Develop and monitor processes related to the full lifecycle of analytical models

Requirements

• Minimum 2 years of experience in MLOps, Machine Learning, or Data Engineering

• Experience with analytics platforms: SAS Viya, Azure ML, Databricks, or Microsoft Fabric

• Python programming skills

• Knowledge of Git and CI/CD processes

• Knowledge of Azure cloud and the Microsoft ecosystem

• Fluent Polish

Benefits

• Project-based B2B cooperation with billing based on stages and acceptance protocols for deliverables

• Administrative and billing support

• Participation in industry events and technology meetups

• Work in Warsaw (approximately 1x per week)

• Referral bonus: 5,000 PLN for referrals to the project(s)

• Flexible B2B form of cooperation and a fast, remote application/process

• AI Recruiter (AIR) application flow with a virtual recruiter available 24/7; final decision made by the Project Owner