This role sits at the intersection of MLOps, traditional data science modeling, and software engineering with opportunities to work on AI/GenAI use cases
Job Summary
This role sits at the intersection of MLOps, traditional data science modeling, and software engineering with opportunities to work on AI/GenAI use cases.
You will collaborate with key stakeholders to translate ambiguous business challenges into structured analyses using statistical modeling and machine learning algorithms.
The position offers a hybrid work model within an international organization that employs approximately 13,000 people across 60 countries.
Matching Summary
This role sits at the intersection of MLOps, traditional data science modeling, and software engineering with opportunities to work on AI/GenAI use cases.
Skills & Requirements
Must-have
Python programming proficiency
Databricks platform experience
Production ML pipeline deployment
MLOps best practices implementation
Model monitoring and versioning
CI/CD for ML workflows
Nice-to-have
GenAI and LLM production experience
RAG and prompt engineering skills
Cross-functional collaboration abilities
Mentoring junior data scientists
Data storytelling capabilities
Adaptability to ambiguous problems
Key Requirements
Bachelor's or master's degree in CS, Engineering, Data Science, Math, or related field
3+ years of experience in Machine Learning Engineering or Applied Machine Learning
Hands-on experience deploying ML models in production environments
Proven ability to operationalize models beyond notebooks