Senior ML Engineer (LLMs, AWS)
Ukraine,Spain,Serbia,Poland,Yerevan
About project
Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.
As an ML Engineer, you’ll be provided with all opportunities for development and growth.
Let's work together to build a better future for everyone!
Requirements:
- Comfortable with standard ML algorithms and underlying math;
- Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems;
- AWS Bedrock experience strongly preferred;
- Practical experience with solving classification and regression tasks in general, feature engineering;
- Practical experience with ML models in production;
- Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines;
- Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts);
- Python expertise, Docker;
- English level - strong Upper- intermediate;
- Excellent communication and problem-solving skills.
Will be a plus:
- Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda);
- Practical experience with deep learning models;
- Experience with taxonomies or ontologies;
- Practical experience with machine learning pipelines to orchestrate complicated workflows;
- Practical experience with Spark/Dask, Great Expectations.
Responsibilities:
- Create ML models from scratch or improve existing models;
- Collaborate with the engineering team, data scientists, and product managers on production models;
- Develop experimentation roadmap;
- Set up a reproducible experimentation environment and maintain experimentation pipelines;
- Monitor and maintain ML models in production to ensure optimal performance;
- Write clear and comprehensive documentation for ML models, processes, and pipelines;
- Stay updated with the latest developments in ML and AI and propose innovative solutions.
What We Offer:
- Long-term B2B collaboration;
- Fully remote setup;
- Comprehensive private medical insurance or budget for your medical needs;
- Paid sick leave, vacation, public holidays;
- Continuous learning support, including unlimited AWS certification sponsorship.
Interview stages:
- Recruitment Interview;
- Tech interview;
- HR Interview;
- HM Interview.