Senior ML Engineer (LLMs, AWS)

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.