Senior ML Engineer IRC302152

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

Requirements

Description

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About Choreograph: A Leading WPP Media Brand

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

Requirements

Essential

• Strong understanding or even hands‑on ML experience,
• Python (needs to be very strong),
• SQL,
• Terraform,
• GCP (esp Vertex, BigQuery, Model Registry),
• Docker,
• FastAPI (or similar),
• Ray
• Airflow / GCP Composer
• Package management (uv is cool, but don’t mind others e.g. poetry; we work with a whole range here),
• Scalable experimentation & model tracking (no specific tech as we’re using native GCP logging and metadata store atm, but as we mature open‑source tech e.g. MLFlow will be brilliant), and
• Scalable ML deployment experience (i.e. standing up an inference endpoint for hardly no traffic doesn’t count)

Desirable

• FTI (Feature/Training/Inference) framework,
• Common ML frameworks (such as PyTorch, Sklearn)

Bonus

• RAG
• LLM orchestration tool e.g LangGraph,
• Reinforcement Learning tools e.g. OpenaiGym, RLib

Job responsibilities

The Machine Learning Engineer is responsible for deploying and maintaining 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. Their work involves implementing, testing, deploying, and monitoring the models in a production environment.

Responsibilities

• Model deployment: Takes models (brand new or improvements to existing models) developed by data scientists and builds the software and infrastructure to deploy them into a live production environment.
• Performance optimization: Optimizes code for latency and efficiency across different hardware, like CPUs and GPUs, and overall quality (e.g. readability, maintainability, reliability and so forth).
• System design & scaling: Designs, builds, and maintains the technical components that integrate into existing software to train, deploy, and scale ML models. (N.B. There will be opportunity to work on new systems from ground up later in the year, too.)
• Monitoring and maintenance: Implements logging and monitoring to track model performance, identifies and fixes bugs (in collaboration with wider teams if appropriate), and performs necessary updates and improvements.
• Collaboration: Works closely with data scientists and wider engineering teams to understand the model and help convert it into a production‑ready system.
• Experimentation: Design, build and deploy technical components based on the methodologies designed by Data Scientists to enable scalable experiments, model evaluation and visualisation of results.
• Up‑skilling DS in ML Engineering and AI innovations: Support DS team to utilise modern and cloud‑based (esp GCP) technologies for development (e.g. Vertex, Docker, BigQuery, Dev Containers, Ray and others) to expedite and innovate the entire development lifecycle –esp when moving from dev into prod

What we offer

• Empowering Projects: With 500+ clients spanning diverse industries and domains, we provide an exciting opportunity to contribute to groundbreaking projects that leverage cutting‑edge technologies. As a team, we engineer digital products that positively impact people’s lives.
• Empowering Growth: We foster a culture of continuous learning and professional development. Our dedication is to provide timely and comprehensive assistance for every consultant through our dedicated Learning & Development team, ensuring their continuous growth and success.
• DE&I Matters: At GlobalLogic, we deeply value and embrace diversity. We are dedicated to providing equal opportunities for all individuals, fostering an inclusive and empowering work environment.
• Career Development: Our corporate culture places a strong emphasis on career development, offering abundant opportunities for growth. Regular interactions with our teams ensure their engagement, motivation, and recognition. We empower our team members to pursue their career goals with confidence and enthusiasm.
• Comprehensive Benefits: In addition to equitable compensation, we provide a comprehensive benefits package that prioritises the overall well‑being of our consultants. We genuinely care about their health and strive to create a positive work environment.
• Flexible Opportunities: At GlobalLogic, we prioritise work‑life balance by offering flexible opportunities tailored to your lifestyle. Explore relocation and rotation options for diverse cultural and professional experiences in different countries with our company.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward‑thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.