EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

We are seeking an experienced Senior MLOps Engineer to join our Enterprise AI Products and Technology Team. The ideal candidate will have industry-relevant experience delivering Machine Learning or Data Science projects at scale.

You will be part of a collaborative team of multidisciplinary engineers, working closely with data science teams, and have the opportunity to create tools, standards, and automate commonly used tasks within the machine learning product lifecycle. A part of the role is also to enhance the capabilities of the platforms team to better align with the data scientist’s working methods. Our data science teams undertake major AI initiatives, including clinical trial data analysis, knowledge graph analytics, patient safety systems, deep learning-led medication discovery, and software as a medical device systems.

As an MLOps Engineer, you possess a software engineering mindset focused on automation and agility, while also being able to question and improve the working methods of data science teams.

Responsibilities

Collaborate with Data Scientists and Machine Learning Engineers from across the company to understand their challenges and work with them to build the tools/platforms that underpin their research
Be a part of a high-performing agile team, continuously improving our client’s Machine Learning development environments, platforms and tooling to suit data science initiatives better
Work closely and collaboratively with internal governance and compliance functions, such as Cyber Security and Data Privacy, to secure our estate without obstructing end-user productivity
Adapt standard machine learning methods to exploit modern parallel environments best (e.g., distributed clusters, multicore SMP and GPU)
Champion a "production first mindset" in the data science projects development lifecycle to seamlessly scale exploratory research to production

Requirements

BSc/MSc/Ph.D degree in Computer Science or related quantitative or analytical field
3 years or more of experience building and delivering software using the Python programming language, exceptional ability in other programming languages will be considered
Demonstrable experience in software engineering and automation leveraging DevOps
Prior experience with developing and deploying production-grade machine learning products or exceptional ability in other software engineering domains will be considered
In-depth knowledge and experience with at least one container orchestration framework (Airflow, Argo, Kubeflow, etc) or willingness to learn
Demonstrable experience deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at scale using Infrastructure as Code
Experience working in an Agile team
Experience working with internal security standards and frameworks

We offer