Mlops Engineer in Softserve

WE ARE

SoftServe is a leading technology solutions company specializing in software products, application development, and services. Our mission is to be a valuable partner for our clients (from start-ups to large enterprises) – we measure our success by our client's success. We are a global team passionate about the development of advisory and consulting services. 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.

We are one of the largest teams in Eastern Europe that stood at the origins of Data Science, and we are looking for a Machine Learning Engineer who is interested in operationalizing ML pipelines and bringing them to production. You will design and implement ML end-to-end solutions, create data pipelines and architectures, set up the infrastructure, and optimize existing models.

• Communicating use cases, requirements, and expectations with stakeholders
• Guiding Engineering and Data Science teams on ML systems production lifecycle
• Data Science teams on model operationalization strategies
• Product teams to deliver and operate ML systems
• Implementing end-to-end production pipelines for ML solutions
• Supporting and continuously enhancing ML software infrastructure: CI/CD, data stores, cloud services, network configuration, security, and system monitoring
• Setting up scalable monitoring systems for data pipelines and ML models
• Operationalizing our clients’ AI solutions by leveraging best practices in Machine Learning and MLOps, DevOps, and Software engineering
• Maintaining 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

• Interested in operationalizing ML pipelines and bringing them to production
• Strongly competent in Machine Learning/Deep Learning models and model lifecycle; software engineering, and DevOps/MLOps principles
• A holder of an MS degree in Computer Science, or a related field, with 3+ years of relevant experience
• Skilled in Python (and traditional Python DS/ML stack) and ML solutions design patterns
• Experienced in AI/ML and Data Engineering tools in AWS, GCP, or Azure
• Hands-on with ML operationalization
• Setting up CI/CD/CT pipelines for ML
• Working with Kubeflow, and ML flow
• Experienced with containers and container orchestration platforms (Kubernetes)
• Advanced conversational English, able to express ideas clearly

• Designing and building feature stores
• Hadoop ecosystem and Apache Spark
• Workflow orchestration platforms such as Airflow
• Message queues and streaming platforms
• Java/Scala

• Participate in international events
• Get certifications in cutting-edge technologies
• Have the possibility to work with the latest modern tools and technologies on different projects
• Access strong educational and mentorship programs
• Communicate with the world-leading companies from our logos portfolio
• Work as a consultant on different projects with a flexible schedule