Senior ML Engineer: Production ML on GCP

GlobalLogic; Poland; On-site; PLN 180,000 - 300,000; Full time

Benefits offered by this job

Relocation options

Flexible opportunities

Inclusive culture

Job summary

GlobalLogic, a Hitachi Group Company, is seeking a Machine Learning Engineer to deploy and maintain the algorithms developed by data scientists.

This role will be part of the Optimize Data Science team (3 FTEs plus seconded team of 5 FTEs) While Data Scientists focus on research and model development, the ML Engineer is responsible for the technical infrastructure, scaling, performance optimization, and maintenance of the models.

Qualifications

• Strong understanding or hands-on ML experience.
• Python (very strong).
• SQL.
• Terraform.
• GCP (Vertex, BigQuery, Model Registry).
• Docker.
• FastAPI (or similar).
• Ray.
• Airflow / GCP Composer.
• Package management (uv is cool, but don’t mind others).
• Scalable experimentation & model tracking (MLFlow, etc.).
• Scalable ML deployment experience.

Responsibilities

• Model deployment: Takes models developed by data scientists and builds software and infrastructure to deploy them into a live production environment.
• Performance optimization: Optimizes code for latency and efficiency across CPUs/GPUs.
• System design & scaling: Designs, builds, and maintains components that train, deploy, and scale ML models.
• Monitoring and maintenance: Logs, monitors, and updates models in production.
• Collaboration: Works with data scientists and wider engineering teams.
• Experimentation: Builds components to enable scalable experiments and visualization of results.
• Up-skilling DS in ML Engineering and AI innovations: Supports DS with cloud technologies (GCP, Vertex, Docker, BigQuery, Ray).

Skills

ML experience

Python

SQL

Terraform

GCP

Docker

FastAPI

Ray

Airflow

Package management

MLFlow

Vertex AI

BigQuery

Tools

Vertex AI

BigQuery

MLFlow

Job description

GlobalLogic, a Hitachi Group Company, is seeking a Machine Learning Engineer to deploy and maintain the algorithms developed by data scientists.

This role will be part of the Optimize Data Science team (3 FTEs plus seconded team of 5 FTEs) While Data Scientists focus on research and model development, the ML Engineer is responsible for the technical infrastructure, scaling, performance optimization, and maintenance of the models.