AI/ML Engineering _Associate_Software Engineering

Morgan Stanley•Campus, IL

About The Position

We’re seeking someone to join our team as (Associate) who can partner with the Advanced analytics, Machine learning and Platform team(s), across multiple project areas, and work in collaboration with team(s) in India & NY. The individual would be response for end-to-end development and operationalization of cross-system data flows, data stores and distributed applications for Analytics, AIML and Visualization. The person would also be part of the overall cloud adoption and engineering roadmap and ensure scalable, agile and robust architecture and implementation. Additionally, should be able to work in a dynamic environment with limited or no supervision and should be able to knowledge-share across other team members. Should be comfortable and manage time working with global team on multiple initiatives. WM_Technology Wealth Management Technology is responsible for the design, development, delivery, and support of the technical solutions behind the products and services used by the Morgan Stanley Wealth Management Business. Practice areas include: Analytics, Intelligence, & Data Technology (AIDT), Client Platforms, Core Technology Services (CTS), Financial Advisor Platforms, Global Banking Technology (GBT), Investment Solutions Technology (IST), Institutional Wealth and Corporate Solutions Technology (IWCST), Technology Delivery Management (TDM), User Experience (UX), and the CAO team. Analytics Intelligence & Data Technology Analytics, Intelligence and Data Technology (AIDT) enables and drives strategic data initiatives and business capabilities across Wealth Management. Software Engineering This is Director position that develops and maintains software solutions that support business needs. Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals. At Morgan Stanley India, we support the Firm’s global businesses, with critical presence across Institutional Securities, Wealth Management, and Investment management, as well as in the Firm’s infrastructure functions of Technology, Operations, Finance, Risk Management, Legal and Corporate & Enterprise Services. Morgan Stanley has been rooted in India since 1993, with campuses in both Mumbai and Bengaluru. We empower our multi-faceted and talented teams to advance their careers and make a global impact on the business. For those who show passion and grit in their work, there’s ample opportunity to move across the businesses for those who show passion and grit in their work. Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on…

Requirements

Experience working towards design, architecture, development, and operationalization of data flows across Hadoop eco-system, Spark (Databricks or otherwise), Snowflake and Cloud platform(s)
Understanding of applied Machine Learning (End-to-End) Lifecycle and Operationalizing AIML models in Production (MLOps)
Experience working on cloud platforms – Azure (Databricks, Snowflake), AWS, and their respective offerings
Experience in developing Large scale Distributed data-driven applications leveraging technologies defined above
Experience and understanding across key SQL and NoSQL datastores – HDFS, S3, Snowflake, MongoDB, Splunk as well as In-memory datastores
Proven understanding of the overall Data and Model deployment lifecycle and processing pipelines including orchestration, workflow scheduling tools, monitoring, optimization
Programming Languages – Expertise in Python, Advanced SQL, and Shell (Scripting)
Expertise in Data analytics and Data wrangling through complex and optimized Python / Spark / SQL
Ability to work in Fast paced and Dynamic environment.
Good written and verbal communication skills

Nice To Haves

GenAI Stack Langchain, RAG , Agentic Frameworks always a plus

Responsibilities

Design, Implement and Operationalize distributed, scalable, and reliable data flows that ingest, process, store, and access data at scale in batch / real-time
Develop distributed applications on-prem as well as on Cloud that scale to serve analytics, rules, web-applications, ML models and Visualizations for end-users
Partner with Analytics and AIML teams to develop and analyze features at scale. Provide SME level interface for team members to optimize their workflows, streamline operationalization and reduce time-to-market
Contribute to metadata management, Data modeling and documentation
Contribute to adoption of CI/CD, Data Ops and ML Ops practices within Data analytics, AIML and Visualization domains
Develop libraries to ease development, monitoring and control of data and models
Define and Implement metrics to monitor data flow performance as well as optimize when necessary
Evaluate state-of-art AIML and Analytics centric technologies and prototype solutions to improve our architecture and platform
Explore new data sources and data from new domains

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume