Senior ML Engineer: Production-Grade ML Deployment

GlobalLogic; Kraków; On-site; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Flexible opportunities

Career development

DEI matters

Comprehensive benefits

Relocation & rotation options

Job summary

GlobalLogic is seeking a Machine Learning Engineer in Kraków to deploy and maintain data-driven models, collaborating with data scientists and engineers. You will build scalable ML pipelines, optimize performance, and ensure production readiness across distributed systems.

You will work with cloud-native tools such as Vertex, BigQuery, and containerized deployments, contributing to high-impact projects for global clients while growing your ML engineering skills in a dynamic team.

Qualifications

• Strong understanding or even hands-on ML experience.
• Python (needs to be very strong).
• SQL proficiency.
• Terraform experience.
• GCP expertise (Vertex, BigQuery, Model Registry).
• Docker proficiency.
• FastAPI or similar framework experience.
• Ray.
• Airflow / GCP Composer.
• Experience with package management tools and ML experimentation tracking.
• Experience deploying ML models in production.

Responsibilities

• Model deployment: build software and infrastructure to deploy models into production.
• Performance optimization for latency and efficiency on CPUs/GPUs.
• Design, build, and scale ML components integrated with existing software.
• Monitoring and maintenance of models and infra.
• Collaborate with data scientists and wider teams to productionize models.
• Enable scalable experiments and model evaluation with visualization.
• Support DS in leveraging cloud-based tools (GCP) to accelerate development.

Skills

ML experience

Python

SQL

Terraform

GCP

Docker

FastAPI

Ray

Airflow

Package management

MLFlow

ML deployment

Tools

BigQuery

Vertex AI

Model Registry

Docker

Kubernetes

Job description

GlobalLogic is seeking a Machine Learning Engineer in Kraków to deploy and maintain data-driven models, collaborating with data scientists and engineers. You will build scalable ML pipelines, optimize performance, and ensure production readiness across distributed systems.

You will work with cloud-native tools such as Vertex, BigQuery, and containerized deployments, contributing to high-impact projects for global clients while growing your ML engineering skills in a dynamic team.