Senior Generative AI Engineer (LLMs)

• 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, and public holidays
• Continuous learning support, including unlimited AWS certification sponsorship

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
• Experience with data pipelines
• English level - strong 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