Machine Learning Engineer

Quick Facts

• Role: Machine Learning Engineer (hands-on ML/Data Science)

• Collaboration: Hybrid in Warsaw (1x every 2 weeks in office)

• Project language: English

• Duration: 12 months (possible extensions)

• Contract: B2B

Description

You will design, build, deploy, and maintain production ML and data processing solutions. The work includes creating data processing pipelines with Apache Spark, preparing and deploying ML models, analyzing performance bottlenecks, and optimizing for cost and efficiency. You will also integrate solutions via REST APIs and support container-based deployments with basic DevOps tasks.

Responsibilities

• Design and implement Machine Learning / Data Science solutions

• Build and evolve data processing pipelines using Apache Spark

• Prepare ML models and deploy them to production environments

• Maintain and develop existing production solutions

• Analyze performance and identify bottlenecks

• Optimize processes for performance and cost

• Work with large datasets and write SQL queries

• Create and integrate solutions through REST APIs

• Work with containers and perform basic DevOps tasks

• Collaborate with technical teams on end-to-end solution development

Requirements

• Minimum 5 years of commercial experience in Machine Learning / Data Science / ML Engineering

• Practical experience deploying and maintaining ML solutions in production

• Very good Python knowledge, including pandas, scipy, and matplotlib

• Practical experience with Apache Spark

• Solid classical Machine Learning experience

• Good SQL knowledge with ability to write queries independently

• Experience with Azure Synapse

• Basic DevOps knowledge: Docker, Kubernetes, container setup/management, basic administrative tasks

• Knowledge of REST APIs

• Good understanding of machine learning concepts