Python Agile DevOps Machine Learning Office

We are looking for an ML Ops Engineer to join our Enterprise AI Products and Technology Team. The ideal candidate will have industry-relevant experience delivering at scale Machine Learning or Data Science projects. You will be part of a collaborative...
We are looking for an ML Ops Engineer to join our Enterprise AI Products and Technology Team. The ideal candidate will have industry-relevant experience delivering at scale Machine Learning or Data Science projects.

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

As an ML Ops engineer, you have a software engineering mindset towards automation and agility while being able to question and improve the ways of working of data science teams.

Work flexibly from anywhere in Spain, with three days a week in our Madrid office to collaborate closely with the team.

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 better suit data science initiatives
- 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 best exploit modern parallel environments (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/Benefits

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

EPAM is a leading digital transformation services and product engineering company with 61,700+ EPAMers in 55+ countries and regions. Since 1993, our multidisciplinary teams have been helping make the future real for our clients and communities around the world. In 2018, we opened an office in Spain that quickly grew to over 1,450 EPAMers distributed between the offices in Málaga, Madrid and Cáceres as well as remotely across the country. Here you will collaborate with multinational teams, contribute to numerous innovative projects, and have an opportunity to learn and grow continuously.

- Why Join EPAM
- WORK AND LIFE BALANCE. Enjoy more of your personal time with flexible work options, 24 working days of annual leave and paid time off for numerous public holidays.
- CONTINUOUS LEARNING CULTURE. Craft your personal Career Development Plan to align with your learning objectives. Take advantage of internal training, mentorship, sponsored certifications and LinkedIn courses.
- CLEAR AND DIFFERENT CAREER PATHS. Grow in engineering or managerial direction to become a People Manager, in-depth technical specialist, Solution Architect, or Project/Delivery Manager.
- STRONG PROFESSIONAL COMMUNITY. Join a global EPAM community of highly skilled experts and connect with them to solve challenges, exchange ideas, share expertise and make friends.

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