Back to SearchSenior Machine Learning Engineer
We are looking for a remote Senior Machine Learning Engineer to join our team.
As a Senior Machine Learning Engineer, you will be responsible for leading and driving innovative projects related to automatic structuring and understanding of unstructured content for our projects. You will be tasked with refactoring, extending, and improving Contaminant ID's model, algorithms, and MLOps so as to follow best practices and increase its autonomy as a product.
Responsibilities
- Lead and drive innovative projects related to automatic structuring and understanding of unstructured content for our projects
- Design efficient deep learning-based solutions and ensure high-quality deliverables
- Refactor, extend, and improve Contaminant ID's model, algorithms, and MLOps so as to follow best practices and increase its autonomy as a product
- Update dependencies and replace OSS libraries that cannot be commercialized, containerize the solution, and help set up CI/CD pipelines
- Improve NFR aspects of the solution, such as security and modularity, and consult with the original developers of the prototype solution to productize it
Requirements
- At least 3 years of industry experience as a Machine Learning Engineer with a focus on scientific research, experimentation, and optimal design
- Strong proficiency in TensorFlow/Python servers, JavaScript for web portal, Tableau for reporting, MariaDB for data storage, Filesystem for video storage, and Docker/Kubernetes for deployment
- Proven experience in refactoring or rewriting parts of existing Python/TensorFlow code, updating dependencies and replacing OSS libraries that cannot be commercialized, containerizing the solution, and setting up CI/CD pipelines
- Familiarity with NFR aspects of a solution, such as security and modularity, and ability to improve them
- Ability to document the new code design and comment on the implementation
- B2+ English level
Nice to have
- Familiarity with AWS, Terraform, and Ansible
- Experience with GPU acceleration and parallel computing
- Familiarity with Natural Language Processing (NLP) techniques
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