Vinay Poduval
@vinaypoduval
Software engineer building scalable distributed systems, microservices, and ML platform infrastructure.
What I'm looking for
I am a software engineer with over 4 years of experience designing and building scalable distributed systems and microservices, focused on reliability and performance. I specialize in Python, Node.js, Go, containerization with Docker, and orchestration with Kubernetes.
At Dream11 I led development of an ML Platform supporting diverse ML and data-science use cases for 100M+ users, engineered a compute service to provision large Ray clusters in under 15 minutes, and implemented autoscaling of disk volumes to raise job success rates to 99.5%.
I also automated benchmarking and developer tooling for high-throughput GraphQL workloads, and have experience building serverless workflows, mentoring teammates, and driving best practices in cloud-native environments.
Experience
Work history, roles, and key accomplishments
Software Development Engineer
Dream11
Jul 2024 - Present (1 year 3 months)
Spearheaded development of Dream11's ML platform supporting 100M+ users, built a Python/Go compute service to provision Ray clusters (up to 12 TB RAM, 1,000+ cores) in <15 minutes, and implemented auto-scaling of disk volumes to raise job success rate to 99.5%.
Software Development Engineer
Dream11
Sep 2021 - Jul 2024 (2 years 10 months)
Automated benchmarking for top 10 high-throughput GraphQL queries reducing profiling time from 1 day to <15 minutes and improved developer velocity via test automation, schema change detection, and MIS reporting.
Software Engineer
Cloudify Solutions
Feb 2021 - Sep 2021 (7 months)
Developed production-grade serverless workflows in Node.js for European clients integrating with Cloudify's Lighthouse product and mentored new team members to improve code quality and collaboration.
Education
Degrees, certifications, and relevant coursework
University of Pune
Bachelor of Engineering, Computer Science
2016 - 2020
Grade: CGPA 8.67/10
Completed a Bachelor of Engineering in Computer Science with a CGPA of 8.67/10, covering core subjects in software engineering and distributed systems.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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