Morgan Stanley Wealth Management (MSWM) Technology is seeking a Machine Learning Engineer to join their Databricks platform team. The role is responsible for architecting, optimizing, and prototyping new features on the Databricks data platform, driving innovation and bringing new ideas to improve efficiency, scalability, and performance of ML models and integrate them into business processes.
Requirements
- Must be strong in UNIX Shell, Python scripting knowledge
- Must be strong in Databricks
- Must have strong knowledge of SQL
- Should have working knowledge of Github, DevOps, CICD/ Enterprise code management tools
- Good to have working experience on Databricks & any data integration tool, etc
- Databricks
- Snowflake
Responsibilities
- Design, develop, and optimize machine learning models to improve efficiency, scalability, and performance.
- Implement innovative MLOps practices to streamline model deployment, monitoring, and maintenance.
- Collaborate with cross-functional teams to integrate ML solutions into business processes.
- Develop and enforce governance frameworks for ML systems, ensuring compliance with ethical and regulatory standards.
- Stay updated on the latest advancements in ML technologies and incorporate them into existing workflows.
- Conduct research and experimentation to identify new approaches for improving model performance and efficiency.
- Document and communicate technical concepts and solutions to both technical and non-technical stakeholders.
Other
- Strong sense of ownership and ability to drive solutions.
- Ability to lead initiations/Proof of concepts in Databricks data platform and bring new ideas and innovation.
- Self-motivated team player committed to delivering on time and should be able to work with or without minimal supervision.
- Strong collaboration and communication skills
- Must possess strong team-player skills and should have excellent written and verbal communication skills
