We are looking for a Cloud Engineer tojoin our new Enterprise AI platform team.

This is an exciting opportunity to be part of a high-impact, highly technical group focused on solving some of the most challenging machine learning problems in the Life Sciences & Healthcare industry. You will bring proven experience in AWS cloud environments and a strong track record of designing and deploying large-scale production infrastructure and platforms.

You will play a critical role in shaping how we use technology, machine learning and data to accelerate innovation. This includes designing, building and deploying next-generation data engines and tools at scale.

This is a hybrid role, with the expectation of occasional office visits in Barcelona.

RESPONSIBILITIES- Develop and maintain the essential infrastructure and platform required to deploy, monitor and manage ML solutions in production, ensuring they are optimized for performance and scalability
- Collaborate closely with data science teams in developing cutting edge data science, AI/ML environments and workflows on AWS
- Liaise with R&D data scientists to understand their challenges and work with them to help productionize ML pipelines, models and algorithms for innovative science
- Take responsibility for all aspects of software engineering, from design to implementation, QA and maintenance
- Lead technology processes from concept development to completion of project deliverables
- Liaise with other teams to enhance our technological stack, to enable the adoption of the latest advances in Data Processing and AI

REQUIREMENTS- Significant experience with AWS cloud environments is essential. Knowledge of SageMaker, Athena, S3, EC2, RDS, Glue, Lambda, Step functions, EKS and ECS is also essential
- Modern DevOps mindset, using best DevOps tools, such as Docker and Git
- Experience with infrastructure as code technology such as Ansible, Terraform and Cloud Formation
- Strong software coding skills, with proficiency in Python, however exceptional ability in any language, will be recognized
- Experience managing an enterprise platform and service, handling new client demand and feature requests
- Experience with containers and microservice architectures e.g., Kubernetes, Docker and serverless approaches
- Experience with Continuous Integration and building continuous delivery pipelines, such as CodePipeline, CodeBuild and Code Deploy
- GxP experience
- Excellent communication, analytical and problem-solving skills

NICE TO HAVE- Experience building large scale data processing pipelines e.g., Hadoop/Spark and SQL
- Use of Data Science modelling tools e.g., R, Python and Data Science notebooks (e.g., Jupyter)
- Multi cloud experience (AWS/Azure/GCP)
- Demonstrable knowledge of building MLOPs environments to a production standard
- Experience on mentoring, coaching and supporting less experienced colleagues and clients
- Experience with SAFe agile principles and practices

WE OFFER- Private health insurance
- EPAM Employees Stock Purchase Plan
- 100% paid sick leave
- Referral Program
- Professional certification
- Language courses