Platform Engineer

• 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

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., * 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, * 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

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

full_time

Organization EPAM Systems

We help our customers navigate the waves of digital transformation, building solutions that help them stay competitive through constant market disruption. As consultants, designers, architects, engineers and trainers, at EPAM we focus on building long-term partnerships with our customers, enabling them to reimagine their businesses through a digital lens. By delivering solutions through best-in-class engineering, strategy, design, consulting, education and innovation services, we help our customers become faster, more agile and more adaptive enterprises. Selected by Newsweek as a 2021 Most Loved Workplace, our global multi-disciplinary teams serve customers in more than 45 countries across five continents. We are listed among the top 15 companies in IT Services on the Fortune 1000 and ranked as the top IT services company on Fortune’s 100 Fastest-Growing Companies list for the last three consecutive years. EPAM is also listed among Ad Age’s top 25 World’s Largest Agency Companies and in 2020, Consulting Magazine named EPAM Continuum a top 20 Fastest-Growing Firm.