Position: Lead Machine Learning Engineer
Company: EPAM Systems
Experience required: 5y
Category: Data Science
English level: upper
Published: 2022-08-01T00:00:00+03:00

The Principal AI/ML Engineer will be responsible for initiating, developing, and deployment of data science solutions/products in an agile fashion to meet demand across multiple business lines. They will also be accountable for adhering to customer quality standards for producing digital solutions.

Key Characteristics
·       Lead a portfolio of programs in IDA 
·       Lead a small team of AI Engineers allocated to the project
·       Working within the Data Science and ML team to deploy models to production, using existing and emerging methods and technologies that could be effectively applied to customer use cases 
·       Build core infrastructure around feature engineering, model training, model deployment, ongoing monitoring tools, and much more.
·       Build and automate our AI/ML workstream from data analysis, experimentation, operationalization, model training, and model tuning to visualization.
·       Work closely with Infrastructure, data engineering, and DevOps teams to increase deployment velocity, including the process for deploying models and data pipelines into production
·       Work closely with Product Management to translate product requirements into robust, customer-agnostic machine learning architectures
·       Keep abreast of new engineering practices, technologies and continuously improve our Agile practices, and building and strengthen relationships and alliances in academia, IDT, and industry 
·       Contribute to community-building initiatives 

Professional Qualifications & Skills 
Required Skills
·       Experience in running portfolios or programs & leading small teams
·       Excellent leadership skills
·       Solid experience in System design of large Machine Learning Applications
·       8+ years of development competency across a breadth of languages, frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Scala, Reactive Streams, Kafka (Python preferred)
·       Solid experience in designing applications using Azure Machine Learning Services.
·        8+ years of experience in designing, developing, deploying, and monitoring machine learning and deep learning solutions.
·       8+ years of experience in Application development, deployment, and monitoring on Kubernetes
·       8+ years of experience in cloud Application Development using AWS or Azure
·       8+ years of experience implementing, Improving, and maintaining automated CI/CD pipeline
·       6+ years of experience working with data scientists and/or ML engineers and building auto-scaling ML systems.
·       Development competency in data engineering and storage, including across a breadth of tools such as S3, RDS, EFS, ADLS Gen2, Azure SQL, Azure Cosmos, ADF, No-SQL