Transforming the way thousands of global organizations do business by developing the most innovative technologies and processes in Big Data, 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, so you will get tons of experience while working with the best talents in the field.
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!
A Machine Learning Architect who is interested in building and delivering AI / ML-powered solutions. You will help us design and implement ML and data pipelines, solution infrastructure, and lead product teams.
You should be strongly competent in Machine Learning / Deep Learning models and model lifecycle, have a solid knowledge of DevOps / MLOps principles and solution architecture, and a good understanding of ML product teams' collaboration models.
A candidate should demonstrate such experience and abilities as
MS degree in computer science or related field
5+ years of relevant experience including 2+ years of design and implementation of enterprise-scale AI / ML solutions in AWS, GCP, or Azure clouds
Designing sustainable architectures, performing trade-off analysis of different architecture tactics and patterns, and applying proven architecture design approaches and methodologies
Customer-facing experience of discovery, assessment, execution, and operations
Hands-on experience in ML operationalization
Driving projects roll-outs from requirements gathering to go-live
Kubernetes platform and its design patterns
Strong requirements gathering and estimation
Upper-Intermediate English level or higher
Your extra power is having a certification / experience in
Relevant Cloud Architecture certification from any of the three major cloud platforms (AWS, Azure, or GCP)
Pre-sales or enterprise consulting
Building solutions with Kubeflow, MLflow, or similar
Hadoop ecosystem and Databricks
Workflow orchestration platforms like Airflow
Designing and building feature stores
Message queues and streaming platforms
YOU WANT TO
Bring your deep expertise in cloud architecture or DevOps to analyze and recommend enterprise-grade solutions for operationalizing AI / ML analytics
Develop end-to-end (Data / Dev / ML)Ops pipelines based on the in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably
Prototype and demonstrate solutions for clients in customer environments
Use your judgment to craft solutions to complex problems or seek guidance as needed
Develop assets, accelerators, and thought capital for your practice
Stay current on new products that clients could use
Communicate use cases, requirements, and expectations with stakeholders
Guide Engineering and Data Science teams on ML systems production lifecycle
Guide Data Science teams on model operationalization strategies
Educate Product teams on best practices for putting ML systems in production
TOGETHER WE WILL
Operationalize our clients’ AI solutions by leveraging best practices in DevOps, Machine Learning, and Solution Architecture
Maintain synergy of Data Scientists, DevOps team, and ML Engineers to build infrastructure, set up processes, productize machine learning pipelines, and integrate them into existing business environments
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