This role sits at the intersection of MLOps, traditional data science modeling, and software engineering to productionize ML and emerging GenAI solutions
Job Summary
This role sits at the intersection of MLOps, traditional data science modeling, and software engineering to productionize ML and emerging GenAI solutions.
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 to productionize ML and emerging GenAI solutions.
Skills & Requirements
Must-have
Python programming proficiency
Databricks platform experience
Production ML pipeline deployment
MLOps best practices implementation
Model monitoring and versioning
Nice-to-have
GenAI and LLM integration experience
Strong data storytelling abilities
Mentoring junior data scientists
Experience with Bitbucket CI/CD
Cloud infrastructure knowledge (AWS)
Key Requirements
Bachelor's or master's degree in CS, Engineering, Data Science, or Math
3+ years of experience in Machine Learning Engineering or Applied ML
Proven ability to build and operate production-grade software systems