Senior Machine Learning Engineer
We are seeking a highly skilled Senior Machine Learning Engineer to join our remote team. As a Senior Machine Learning Engineer, you will be responsible for designing and implementing machine learning solutions for our clients using your extensive experience in Data Science and Machine Learning Engineering. You will be working with large-scale datasets and using your expertise to develop and deploy industrial-scale ML solutions. You will also be responsible for communicating with client stakeholders on both the technical and business side to ensure delivery is client driven. If you have a passion for designing and implementing machine learning solutions, we encourage you to apply.
Responsibilities
- Design and implement machine learning solutions for clients using your expertise in Data Science and Machine Learning Engineering
- Work with large-scale datasets and develop and deploy industrial-scale ML solutions
- Communicate with client stakeholders on both the technical and business side to ensure delivery is client driven
- Integrate ML solutions into cloud services such as AWS SageMaker, S3, and Lambda
- Analyze and interpret data and provide clear and comprehensive reports
- Collaborate with cross-functional teams to conceptualize, design, develop, and implement effective machine learning solutions
Requirements
- 3+ years of experience in Data Science and Machine Learning Engineering
- Strong understanding of Amazon Web Services (AWS) and experience with AWS SageMaker, S3, Lambda, and other cloud services
- Experience in time series forecasting and working with R-based solutions
- Experience with orchestration and experiment tracking tools such as AirFlow, MLFlow, and DVC
- Ability to communicate effectively with client stakeholders on both the technical and business side
- Fluent English language skills with an Upper-Intermediate level as a minimum
Nice to have
- Experience with Snowflake, R time series libraries, AWS CodePipeline, DataBricks, and k8s
Benefits
- International projects with top brands
- Work with global teams of highly skilled, diverse peers
- Healthcare benefits
- Employee financial programs
- Paid time off and sick leave
- Upskilling, reskilling and certification courses
- Unlimited access to the LinkedIn Learning library and 22,000+ courses
- Global career opportunities
- Volunteer and community involvement opportunities
- EPAM Employee Groups
- Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn