MLOps Engineer

With over 25 years of experience in the industry, NEORIS an EPAM Company offers a specialized technical career path to support and develop its most valuable asset: its people. Our goal is to continue growing, and to achieve that, we want you to join us and help us improve every day.

We’re expanding our teams and looking for individuals who share our culture and values, including responsibility, collaboration and teamwork, creativity, and dedication. If you’re passionate about continuous learning, specialization, and contributing to projects using the latest technologies, don’t hesitate to get in touch with us.

Moreover, our evaluation processes focus on professionals’ experience and knowledge, as well as their motivation and soft skills. We are committed to inclusion and provide equal employment opportunities.

 

🎯 We are looking for: MLOps engineer

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 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 ways of working. 

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

 

🖥️ Key responsabilities:

• 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 underpins their research.
• Be a part of a high performing agile team, continuously improving Machine Learning development environments, platforms and tooling to better suite 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

 

👩‍💻 Must have skills:

• Demonstrable experience in software engineering and automation leveraging DevOps.
• Prior experience with developing and deploying production grade machine learning products.
• Demonstratable experience deploying the underlying infrastructure and tooling for running Machine Learning or Data Science at Scale using Infrastructure of Code.
• Python.ML
• Amazon Web Services/Azure/GCP
• Kubernetes
• GitHub actions
• IaC - a good to have but will prioritise if you have.
• Machine Learning - Good to have exposure

🛠️ Nice to have skills:

• IaaS
• Google Cloud Platform
• Microsoft Azure
• Terraform
• Agile

 

🌟What we offer:

 

• Innovative Projects: Work on transformative, high-impact projects that matter.
• Career Growth: Develop your career with continuous learning, training, and a culture that promotes from within.
• Culture: We’re committed to diversity, inclusion, and providing equal opportunities for all. We care about your experience, knowledge, and soft skills.
• Work-Life Balance: We understand the importance of balance and offer flexible work arrangements to suit your lifestyle.

 

 

Ready to make an impact with us? 🚀

If you’re ready to challenge yourself and help us deliver innovative solutions for clients worldwide, we want to hear from you!

 

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