AI/ ML Ops Engineer

Morgan Stanley • New York, NY

1d

About The Position

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Lead Data & Analytics Engineering position at the Director level, which is part of the job family responsible for providing specialist data analysis and expertise that drive decision-making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI-based techniques. 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. Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on. Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. We advise, originate, trade, manage and distribute capital for governments, institutions and individuals. As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. We provide you a superior foundation for building a professional career where you can learn, achieve and grow. Wealth Management Technology (WMIMT) is responsible for the design, development, delivery, and support of the technical platform behind the products and services used by the Business. Morgan Stanley Wealth Management (WM) is a product of the acquisition of Smith Barney from Citigroup, which was completed in June '13. Its core client base is individual investors, small- to medium-size businesses and institutions, and high net worth families and individuals. In the second half of '14, WM reached a milestone, with its business having surpassed $2 trillion in total client assets. We're seeking someone to join our team as (Director) 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 along with stakeholder management. 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. Analytics, Intelligence and Data Technology (AIDT) enables and drives strategic data initiatives and business capabilities across Wealth Management.

Requirements

• Minimum B.E./B.Tech degree in Computer Science, Engineering, or a related field.
• 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 is 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 analyse 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 modelling 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Director