Senior AI/ML Engineer (GenAI, AWS)

Provectus; Kraków; On-site; PLN 180,000 - 280,000; Full time

Job summary

Provectus is seeking an ML Engineer to build and maintain cutting‑edge ML models and pipelines. You will collaborate with engineers, data scientists, and product managers to ship production models and define an experimentation roadmap.

You will set up reproducible environments, monitor production performance, and document models and processes while staying current with ML/AI advances and proposing innovative solutions.

Qualifications

• Proficient with standard ML algorithms and underlying math.
• Hands-on production experience with LLMs, RAG, and agentic systems.
• Experience with AWS Bedrock strongly preferred.
• Experience solving classification and regression tasks and feature engineering.
• Experience with ML models in production and NLP/LLMs/Recommendation use cases.
• Solid software engineering skills for modular, production-ready code.
• Proficient in Python and Docker.
• Excellent communication and problem-solving skills.

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.

Skills

ML algorithms

Math fundamentals

Production ML

NLP/LLMs

Agentic systems

Problem solving

Communication

English (upper-intermediate)

Tools

Python

Docker

AWS Bedrock

SageMaker

Spark

Dask

Great Expectations

Job description

Join us at Provectus to be a part of a team that is dedicated to building cutting‑edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

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!

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.

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.

Nice to Have

• 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.