Senior MLOps Engineer

Key Skills

Aartificial intelligence, Apache Airflow, AWS, Azure, Big Data Technology, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, DevOps, Effective communication skills, Google Cloud Platform (GCP), Machine learning techniques, MLOps tools, Python Programming, SPARK Programming

Job Description

WE ARE

SoftServe is a global digital service and consulting company founded in 1993. We're working on 1,100+ projects with clients in the USA, Europe, APAC, and LatAm regions. SoftServians help transform, accelerate, and optimize how our clients, including ISVs and Fortune 500 companies, do business.

Our Data Science Group is one of the largest teams (80+ specialists) in Eastern Europe that stood at the origins of Data Science, so you will get tons of experience while working with the best talents in the field. We are transforming the way thousands of global organizations do business by developing the most innovative technologies and processes in Big Data, the Internet of Things (IoT), Data Science, and Experience Design.

In a Data Science Center of Excellence, you will have a chance to contribute to a wide range of projects in different areas and technologies. We are looking for a person who is inspired by data, analytics, and AI as much as we are, and who wants to grow with us!

IF YOU ARE

• A MS degree holder in Computer Science or a related field, and 3+ years of relevant experience
• Strong in Python and traditional Python DS/ML stack
• Experienced in ML solutions design patterns
• Confident with AI/ML and Data Engineering tools in any major cloud platform: GCP, AWS, or Azure
• Proficient in ML operationalization
• Effective in setting up CI/CD/CT pipelines for ML
• Skilled in Kubeflow, MLflow, or similar
• Competent in containers and container orchestration platforms (Kubernetes)
• Accustomed to making strong requirements gathering and estimation
• Able to maintain business communication and conduct presales activities with English-speaking clients
• Able to design and build feature stores (would be a plus)
• Familiar with the Hadoop ecosystem and Apache Spark (as an advantage)
• Aware of workflow orchestration platforms such as Airflow (as an extra point)
• Skilled in message queues and streaming platforms (nice-to-have knowledge)
• Familiar with Java/Scala (is not a must)

AND YOU WANT TO

• Design and implement ML end-to-end solutions, create data pipelines and architectures, set up the infrastructure, and optimize existing models
• Communicate about use cases, requirements, and expectations with stakeholders
• Guide Engineering and Data Science teams on ML systems production lifecycle
• Work with Data Science teams on model operationalization strategies
• Be a part of product teams to deliver and operate ML systems
• Implement end-to-end production pipelines for ML solutions
• Support and continuously enhance ML software infrastructure: CI/CD, data stores, cloud services, network configuration, security, and system monitoring
• Set up scalable monitoring systems for data pipelines and ML models

TOGETHER WE WILL

• Operationalize our clients’ AI solutions by leveraging best practices in Machine Learning and MLOps, DevOps, and Software engineering
• Maintain synergy of Data Scientists, DevOps team, and ML Engineers to build infrastructure, set up processes, and Machine Learning pipelines, and integrate them into existing business environments
• Gain certifications from leading providers (Google, AWS & others)
• Have the possibility to work with the latest modern tools and technologies on different projects
• Communicate with the world-leading companies from our logos portfolio
• Work as a consultant on different projects with a flexible schedule