Pranav Dhingra
AI Product Manager
Building intelligent systems at scale. Technical PM with software engineering background, specializing in ML-powered products.
About Me
I'm currently pursuing a Master of Engineering in Computer Science at Cornell Tech, exploring the AI product development lifecycle and building end-to-end AI solutions.
As a Senior Product Manager at Grubhub, I led the product vision, strategy, and roadmap for timing and estimation (ETAs) across the food delivery platform. I leveraged my technical skillset and domain expertise to find opportunities and build solutions in a complex and dynamic problem space, working with delivery engineering, experimentation, and machine learning teams.
I started my career as a Software Engineer at Grubhub, where I built and maintained microservices for auto-dispatch and experimentation, handling up to 400,000 requests per minute. This technical foundation gives me a unique perspective as a product manager—I understand both the strategic vision and the engineering complexity required to ship ML-powered products at scale.
I graduated from Northwestern University with a double major in Computer Science and Economics. I enjoy working with people of all technical abilities to deliver value to users and stakeholders.
Impact at Scale
Delivering measurable results through data-driven product decisions and technical execution
Annual Cost Savings
Coordinated ETA interventions with auto-dispatch algorithm
Orders Generated
Priority Delivery feature with 46% adoption rate
Error Reduction
Improved restaurant food prep estimates with new ML models
Fewer Late Deliveries
ETA display experimentation with 15-minute ranges
Requests/Minute
Built experimentation microservice handling high volume
Experience
Master of Engineering, Computer Science
Cornell Tech
Exploring AI product development lifecycle, ML engineering, deep learning, and trustworthy AI.
Key Highlights
- Applied ML
- ML Engineering
- Deep Learning
- Trustworthy AI
Senior Product Manager
Grubhub
Led delivery engineering and data science teams to develop ML-powered features.
Key Highlights
- Led Priority Delivery feature (550K+ orders, 46% adoption)
- Achieved $49.5M annual cost savings through ETA optimization
- Reduced late deliveries by 9.28% with experimentation
- Improved ML model accuracy by 50% for food prep estimates
Product Manager II
Grubhub
Set product vision, strategy, and roadmap for timing and estimation (ETAs) across Grubhub.
Key Highlights
- Introduced real-time market condition-based ETAs (+1.6% CTR, $4M revenue)
- Enabled diner/visitor-level A/B testing for ETAs
- Reduced driver wait time by 2.9%
Software Engineer II
Grubhub
Built experimentation microservice and maintained auto-dispatch systems.
Key Highlights
- Built experimentation microservice (400K req/min, <10ms SLO)
- Primary code-owner for experiment administration service
- Architected high-volume client integrations
Software Engineer I
Grubhub
Built and maintained features for auto-dispatch microservices.
Key Highlights
- Maintained auto-dispatch for 500K+ daily deliveries (700K+ at peak)
- Implemented real-time monitoring for courier-supply issues
- Created dashboards for delivery insights using PrestoSQL
Algorithm Engineer Intern
Trax Retail
Worked with Computer Vision group on deep learning models for retail.
Key Highlights
- Built debugging tool for deep networks using feature visualization
- Improved model interpretability with saliency maps
- Created error metric dashboards in TensorBoard
B.A. Computer Science & Economics
Northwestern University
Double major in Computer Science and Economics. Teaching Assistant for AI and programming courses.
Key Highlights
- TA for AI, Programming, and Visualization courses
- Tech Lead for Entrepreneurship in Action (EPIC)
- Federal Reserve Challenge Team - National Finalists
Master of Engineering, Computer Science
Cornell Tech
Exploring AI product development lifecycle, ML engineering, deep learning, and trustworthy AI.
Key Highlights
- Applied ML
- ML Engineering
- Deep Learning
- Trustworthy AI
Senior Product Manager
Grubhub
Led delivery engineering and data science teams to develop ML-powered features.
Key Highlights
- Led Priority Delivery feature (550K+ orders, 46% adoption)
- Achieved $49.5M annual cost savings through ETA optimization
- Reduced late deliveries by 9.28% with experimentation
- Improved ML model accuracy by 50% for food prep estimates
Product Manager II
Grubhub
Set product vision, strategy, and roadmap for timing and estimation (ETAs) across Grubhub.
Key Highlights
- Introduced real-time market condition-based ETAs (+1.6% CTR, $4M revenue)
- Enabled diner/visitor-level A/B testing for ETAs
- Reduced driver wait time by 2.9%
Software Engineer II
Grubhub
Built experimentation microservice and maintained auto-dispatch systems.
Key Highlights
- Built experimentation microservice (400K req/min, <10ms SLO)
- Primary code-owner for experiment administration service
- Architected high-volume client integrations
Software Engineer I
Grubhub
Built and maintained features for auto-dispatch microservices.
Key Highlights
- Maintained auto-dispatch for 500K+ daily deliveries (700K+ at peak)
- Implemented real-time monitoring for courier-supply issues
- Created dashboards for delivery insights using PrestoSQL
Algorithm Engineer Intern
Trax Retail
Worked with Computer Vision group on deep learning models for retail.
Key Highlights
- Built debugging tool for deep networks using feature visualization
- Improved model interpretability with saliency maps
- Created error metric dashboards in TensorBoard
B.A. Computer Science & Economics
Northwestern University
Double major in Computer Science and Economics. Teaching Assistant for AI and programming courses.
Key Highlights
- TA for AI, Programming, and Visualization courses
- Tech Lead for Entrepreneurship in Action (EPIC)
- Federal Reserve Challenge Team - National Finalists
Featured Projects
Highlights from my work building ML-powered products at scale
Led cross-functional teams to develop a premium delivery feature that generated 550,000+ orders within two months with a 46% diner adoption rate.
Oversaw development of 2 new ML models that improved restaurant food prep estimates by combining predictions of different target variables.
Built experimentation microservice handling 400,000 requests per minute with sub-10ms response time, enabling data-driven product decisions at scale.
Skills & Expertise
Technical depth across product management, engineering, and AI/ML
Let's Connect
I'm currently exploring opportunities in AI Product Management. Feel free to reach out!