Vivek Subramanian

Accomplished Director of Machine Learning Engineering at Fidelity Investments, adept at optimizing machine learning operations and enhancing prediction accuracy. Expert in Python and AWS, with a proven track record in developing automated data pipelines and fostering team collaboration to drive innovative solutions in generative AI and data integration.

• Generative AI Nano Degree
• AWS Certified Solutions Architect – Associate
• AWS Machine Learning Specialty
• AWS Data Analytics Specialty
• Snowflake SnowPro Core Certification
• Analyze Datasets and Train ML Models using AutoML
• Practical Data Science - Coursera
• Astronomer Certification for Apache Airflow Fundamentals
• Confluent Certified Developer for Apache Kafka

Tempus – Forecasting Application - Tempus is a forecasting and simulation platform that supports strategic decision-making across key business domains such as call center staffing, infrastructure capacity planning, and enterprise scenario modeling. The solution integrated machine learning and data engineering to deliver scalable and automated time-series forecasts. Leveraged AWS SageMaker for model deployment, AWS Glue and Lambda for data pipelines, and PySpark for optimization. Data sources included Snowflake, Adobe Analytics, and FRED. 

Fidelity Assistant – Autosuggest

Developed and deployed an NLP-based Autosuggest feature for the FA Assistant chatbot, enabling real-time query suggestions as users typed. Engineered the model pipeline using SageMaker, Python NLP libraries (spaCy, Transformers), and AWS Glue for data processing. Implemented FastAPI middleware and Jenkins CI/CD automation for seamless integration into production.

Fidelity Assistant – Related Questions

Engineered a standalone NLP model to power the Related Questions feature for the FA Assistant chatbot. This component dynamically generated contextually relevant follow-up questions after each user interaction. Built using SageMaker, Glue, and Python-based NLP frameworks, with robust deployment handled via FastAPI endpoints and AWS orchestration.
Next Generation Data Platform

• ML Engineering, Led the deployment of multiple ML models including time-series linear regression and NLP models on AWS SageMaker, enabling real-time forecasting and intelligent chatbot interactions.
• Data Engineering, Architected and implemented Rapid Data reducing data onboarding time and increasing pipeline reliability. Spearheaded cloud migration of brokerage data from mainframe to AWS, transforming legacy infrastructure and enhancing system scalability and agility.
• Analytics, Partnered with stakeholders to translate business needs into analytical models, supporting initiatives in staffing optimization, resource forecasting, and customer service intelligence.
• Project Leadership Excellence, Led 25-member cross-functional team, delivering project under budget and ahead of schedule.

• Product & Strategic Leadership
• Led technical teams supporting agile squads to deliver enterprise-scale ML and data platforms aligned with business goals.
• Contributed to product strategy and technical roadmaps for forecasting, analytics, and NLP chatbot solutions enhancing decision-making and user experience.
• Agile & Technical Team Leadership
• Served as Technical Lead, guiding scrum teams on data engineering and ML ops projects, ensuring quality delivery and technical ownership.
• Mentored onsite and offshore engineers, fostering collaboration and efficient resource planning in Agile environments.
• Technical & Delivery Oversight
• Managed end-to-end delivery of scalable data pipelines and ML model deployments on AWS with CI/CD automation.
• Optimized system performance and reliability using monitoring tools and data workflow enhancements for mission-critical applications.
• Stakeholder Collaboration & Communication
• Collaborated with data scientists and business partners to translate requirements into scalable, maintainable technical solutions.
• Prioritized technical backlog in alignment with business objectives to ensure impactful product delivery.
• Innovation & Continuous Improvement
• Drove adoption of advanced technologies such as SageMaker, PySpark optimizations, and NLP libraries to improve model accuracy and system efficiency.
• Maintained up-to-date knowledge of cloud and ML trends to continuously enhance product capabilities and operational excellence.