Senior MLOps Engineer (AWS Services)

Our requirements

• 10+ years of professional experience with AWS services, including hands-on implementation of cloud-based data and ML solutions.
• Proven experience delivering projects for the banking sector or other highly regulated industries, with an understanding of security, compliance and operational requirements.
• Strong proficiency with MLOps practices: CI/CD for models, automated testing, model monitoring and deployment patterns.
• Experience building distributed data processing systems and pipelines for both structured and unstructured data; familiarity with near real-time processing architectures.
• Practical knowledge of relevant AWS services such as EC2, ECS/EKS, Lambda, S3, Glue, EMR, SageMaker, Kinesis, MSK, RDS/Aurora, IAM and CloudWatch or equivalents.
• Solid programming skills in languages commonly used for ML and data engineering (for example Python, and familiarity with frameworks and tools such as Terraform, Docker, Kubernetes, Spark).
• Experience with security controls, data governance, and operational resilience in cloud environments.
• Bachelor’s degree in Computer Science, Engineering, Data Science or a related discipline, or equivalent practical experience.
• Strong communication skills and the ability to coordinate work across multidisciplinary teams.

Your responsibilities

• Manage the end-to-end lifecycle of machine learning models: development, testing, deployment, monitoring and maintenance.
• Design, build and operate CI/CD pipelines for machine learning artifacts, ensuring automated testing, reproducibility and traceability.
• Implement robust monitoring, alerting and performance optimisation for models and data pipelines in production.
• Architect and develop distributed, highly parallelised big data processing pipelines that handle large-scale structured and unstructured data in near real-time.
• Leverage AWS services (compute, storage, data processing, orchestration and monitoring) to deliver scalable and secure MLOps solutions.
• Collaborate with data scientists, DevOps engineers, IT and security teams to integrate models into enterprise environments and ensure compliance with operational requirements.
• Define and enforce best practices for model versioning, data management, reproducibility and governance.
• Conduct performance tuning, capacity planning and cost optimisation for cloud resources supporting ML workloads.
• Provide technical leadership, mentorship and knowledge sharing across cross-functional teams.

About the project

This is how we work on a project

• documentation
• issue tracking tools
• testing environments

What we offer

• Hybrid work (2 days/week from Warsaw/Gdańsk/Gdynia/Łódź)
• Opportunities for professional development and technical growth within advanced data and cloud projects.
• Collaboration with experienced cross-functional teams on complex, large-scale initiatives in the banking domain.
• Access to modern cloud infrastructure and tools for experimentation and production deployment.
• Support for continuous learning, including technical training and knowledge sharing.
• Unique TEAL culture: relationship- and respect-driven community in a non-corporate atmosphere.
• Agile working model with minimal bureaucracy.
• Company integration trips to various locations in Europe for all employees.
• Activities supporting employee well-being and health.
• Luxmed Gold Extended medical care and Multisport Plus benefit.

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of professional training & courses
• remote work opportunities
• flexible working time
• integration events

YOUR ITEAMS sp. z o.o.