Senior AI/ML Engineer (GenAI, AWS)

Provectus; Madrid; On-site; EUR 60,000 - 90,000; Full time

Job summary

Provectus is hiring an ML Engineer in Madrid to build AI/ML solutions that impact society. You will work on production-grade models, NLP, LLMs, and recommender systems, collaborating with engineers, data scientists, and product managers.

The role emphasizes robust software engineering, documentation, and continuous experimentation. Strong Python and Docker skills, plus upper-intermediate English, are essential for cross-functional teamwork in a fast-moving environment.

Qualifications

• Experience with standard ML algorithms and underlying math.
• Hands-on production experience with LLMs, RAG, and agentic systems.
• AWS Bedrock experience strongly preferred.
• Proven ability with solving classification and regression tasks and feature engineering.
• Production ML model experience.
• Experience with NLP, LLMs, and recommender systems.
• Solid software engineering; modular code beyond notebooks.
• Proficiency in Python and Docker.
• English level: strong upper-intermediate.
• Excellent communication and problem-solving skills.

Responsibilities

• Create ML models from scratch or improve existing models.
• Collaborate with engineering, data science, and product teams on production models.
• Develop experimentation roadmap.
• Set up reproducible experimentation environment and pipelines.
• Monitor and maintain ML models in production for optimal performance.
• Write clear documentation for ML models, processes, and pipelines.
• Stay updated with ML/AI developments and propose innovative solutions.

Skills

Python

Docker

LLMs in production

RAG architecture

Agentic systems

NLP

Recommendation engines

Software engineering

ML algorithms

Math

English (upper-intermediate)

Tools

AWS Bedrock

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!

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

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.