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# Senior ML Engineer (LLMs, AWS)

- **Company:** Provectus
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon S3, Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, Software Engineering, Feature Engineering, Large Language Models, Multi-Agent Systems, Apache Spark, Deep Learning, Electronic Medical Records, AWS Lambda, Dask, Machine Learning Operations, Docker
- **Published:** May 30, 2026
- **Apply:** https://es.indeed.com/viewjob?jk=5c9d8a43e10e0719

## About the Role

Do you have experience in Spark?, * 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., * 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.

## Description

* 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.


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