Ai/ Ml Ops Engineer

Morgan Stanley

New York, United States
Base: $120,000 - $165,000 py; bonus/equity: not sp...
Data pipelines
Machine learning operationalization
Cloud platforms (azure, aws)
Leverage innovation to build connections and capabilities that power the Firm, enabling clients and colleagues to redefine markets and shape the future

Job Summary

  • Leverage innovation to build connections and capabilities that power the Firm, enabling clients and colleagues to redefine markets and shape the future.
  • Partner with Advanced analytics, Machine learning and Platform team(s) to develop and operationalize cross-system data flows, data stores and distributed applications.
  • Contribute to the overall cloud adoption and engineering roadmap, ensuring scalable, agile and robust architecture and implementation.

Matching Summary

Leverage innovation to build connections and capabilities that power the Firm, enabling clients and colleagues to redefine markets and shape the future.

Salary

Base: $120,000 - $165,000 per year; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • Data Pipelines
  • Machine Learning Operationalization
  • Cloud Platforms (Azure, AWS)
  • Distributed Data Applications
  • Python, Advanced SQL, Shell Scripting
  • Data Ops and ML Ops practices

Nice-to-have

  • GenAI Stack (Langchain, RAG)
  • Stakeholder Management
  • Knowledge Sharing
  • Agile and Robust Architecture

Key Requirements

  • Minimum B.E./B.Tech degree
  • Experience with Hadoop ecosystem, Spark, Snowflake
  • Understanding of applied Machine Learning Lifecycle
  • Experience with Azure (Databricks, Snowflake), AWS
  • Experience with SQL and NoSQL datastores
  • Proven understanding of Data and Model deployment lifecycle

Work Rights

Not specified

Tailored Resume

Cover Letter