ITDS

Senior MLOps Engineer – AI Infrastructure & Pipelines

21k - 31.5k PLN21 000 - 31 500 PLN/ mies./ mies.B2BB2B (netto)

MidHybryda·WarszawaFull-time·B2B

#462339·Dodano 15 dni temu·1

Źródło: justjoin.it

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Tech Stack / Keywords

Python CI/CD Docker Kubernetes AWS MLflow Machine Learning ETL Bash TensorFlow

Podsumowanie oferty

Build and operate AI and machine learning infrastructure for a financial institution, automating model lifecycles and deploying systems to production. The role focuses on scalable pipelines and MLOps, using technologies including Python, CI/CD, AWS, Kubernetes and MLflow.

Wymagania

You're ideal for this role if you have:

At least 4 years of experience in MLOps, AI Infrastructure or related engineering fields.
Strong proficiency in Python and scripting languages such as Bash.
Hands-on experience with CI/CD tools such as Jenkins, GitLab CI/CD or similar.
Knowledge of containerization and orchestration technologies, including Docker and Kubernetes.
Experience working with cloud platforms (AWS, Azure or GCP) for machine learning and data pipelines.
Familiarity with machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn.
Deep understanding of data pipelines, ETL processes and workflow orchestration tools.
Experience with model monitoring and observability tools such as MLflow, Prometheus or Grafana.
Fluent written and spoken English.
Fluent written and spoken Polish.

Strong plus:

Certification or hands-on experience with Kubernetes, AWS/Azure certifications, or equivalent.
Knowledge of security and compliance standards relevant to data and AI systems.

Obowiązki

Your main responsibilities:

Design and maintain CI/CD pipelines for machine learning models.
Automate deployment, testing and monitoring of AI solutions in production environments.
Manage cloud infrastructure on AWS, Azure or GCP, and optimize resources for machine learning workloads.
Collaborate with data scientists to ensure reproducibility and scalability of experiments.
Implement model monitoring and performance tracking systems using MLflow, Prometheus or Grafana.
Troubleshoot and resolve production issues to ensure continuous system uptime.
Document workflows, processes and infrastructure configurations.
Apply security, compliance and data governance best practices within AI pipelines.
Support ongoing improvements of MLOps tools, frameworks and processes.
Stay abreast of emerging trends and practices in AI infrastructure and MLOps.

Inne informacje

Only candidates with an existing legal right to work in the European Union will be considered.

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