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Offer summary
(Summary generated by AI based on the full job description)
The project focuses on deploying and maintaining AI/ML solutions in production with emphasis on optimizing GPU environments. Required stack includes Python, PyTorch/TensorFlow, Scikit-learn, Hugging Face, MLOps tools like MLflow/Kubeflow/Azure ML/Vertex AI/SageMaker, CI/CD (GitHub Actions/Azure DevOps/GitLab CI), Docker and Kubernetes, and cloud familiarity with Azure/AWS/GCP. Responsibilities cover designing and developing models, building and maintaining MLOps pipelines, automating training and deployment, monitoring model performance and data drift, managing ML lifecycle, optimizing GPU resource usage, and collaborating with team and producing technical documentation.
from: 12 October 2026
to: 11 November 2026
salary not specifiedcontract of employment (full-time)
Offer parameters
level:mid
working mode:hybrid
Warszawa, Mokotów
Requirements
Operating system
Windows
Our requirements
- Minimum 3 years of experience in AI/ML projects.
- Strong proficiency in Python.
- Hands-on experience with: PyTorch or TensorFlow, Scikit-learn, Hugging Face
- Experience with MLOps technologies: MLflow, Kubeflow, Azure Machine Learning, Vertex AI, or SageMaker, CI/CD tools (GitHub Actions, Azure DevOps, GitLab CI)
- Experience with Docker and Kubernetes.
- Hands-on experience working with distributed AI/ML environments and compute clusters.
- Good understanding of cloud platforms (Azure, AWS, or GCP) or on-premise systems.
- Understanding of workload orchestration, resource allocation, and scaling for machine learning workloads.
- Experience with Git and modern DevOps practices.
- English proficiency at B2 level or higher.
- Strong ownership and accountability for delivered solutions.
- Ability to translate business requirements into technical implementations.
- Analytical mindset with a problem-solving approach.
- Passion for experimenting with emerging AI technologies.
- Strong organizational and collaboration skills in Agile environments.
Optional
- Experience with LLMs and Generative AI solutions.
- Knowledge of RAG, Vector Databases, and Agentic AI.
- Experience with cloud-based GPU platforms (Azure AI, AWS EC2 P4/P5, GCP A3).
- Experience managing or operating GPU-enabled Kubernetes clusters.
- Experience with NVIDIA GPU Operator, KServe, Ray, Kubeflow, or similar technologies.
- Understanding of cluster monitoring and performance optimization in AI environments.
- Familiarity with Spark, Databricks, or Ray.
Your responsibilities
- Design and develop AI and Machine Learning solutions.
- Build and maintain MLOps pipelines (CI/CD for ML models).
- Automate model training, deployment, and monitoring processes.
- Manage the end-to-end machine learning lifecycle (ML Lifecycle Management).
- Collaborate closely with Data Scientists, Software Engineers, and business stakeholders.
- Optimize computational resource utilization, particularly GPU-based environments.
- Monitor model performance, quality, and data drift.
- Contribute to the design of AI architectures on cloud platforms.
- Create technical documentation and establish engineering best practices.
About the project
We are looking for an experienced AI Engineer who will be responsible for designing, deploying, and maintaining AI/ML solutions in production environments. The role combines expertise in Machine Learning Engineering, MLOps, and basic administration and optimization of GPU infrastructure supporting model training and inference workloads.
Recruitment stages
- 1.Let’s meet to better understand each other's expectations.
- 2.Hiring Manager will receive your application after meeting.
- 3.Technical meetings with the Hiring Manager and/or team.
- 4.Time to decide!
T-Mobile
Working at T-Mobile’s T Hub will offer you an unique and highly rewarding experience on IT market. As a leader in the telecommunications industry, T-Mobile not only provides a platform to hone your technical skills but also empowers you to be a catalyst for innovation. You'll have the opportunity to work at the forefront of cutting-edge technologies, from 5G to IoT and AI, shaping the future of connectivity. Our commitment to fostering a diverse and inclusive workplace means you'll collaborate with a wide range of talented professionals, learning and growing together. T-Mobile encourages a culture of continuous learning and development, offering mentorship and support to help you thrive in your career.
This is how we work
T Hub - AI Engineer ML Ops & GPU computing
I apply to:
T-Mobile
Warszawa, Mokotów
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