Abhishek Malvankar
Senior Software Engineer, IBM Research at Cloud Native Computing Foundation (CNCF)
New York City Metropolitan Area United States
Summary
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Rockstar🎓
Top SchoolAbhishek Malvankar is a Senior Software Engineer at IBM Research with 11 years of experience specializing in resource and infrastructure optimization for scale-out AI applications. He focuses on distributed computing, resource management, and performance improvements, driving software engineering efforts that make AI workloads more efficient in production. As Chair of the CNCF Batch System Initiative, he contributes to shaping cloud-native batch systems and bridges research with open-source community practices. His background includes HPC engineering and secure distributed systems work from NYU and industry roles, giving him a pragmatic lens on performance, monitoring, and reliability. Based in the New York City area, he combines research-grade rigor with hands-on systems engineering to optimize real-world AI infrastructure.
11 years of coding experience
3 years of employment as a software developer
SSC, SSC at Lourdes High School,KalyanBachelor of Engineering, Electronics and telecommunication, Bachelor of Engineering, Electronics and telecommunication at University of MumbaiDiploma, Electronics and Telecommunications, Diploma, Electronics and Telecommunications at Institute of Technology,MSBTEMaster's degree, Computer Engineering, Master's degree, Computer Engineering at New York UniversityB.E., Electronics and telecommunication, B.E., Electronics and telecommunication at K.J. Somaiya College of Engineering
English
Github Skills (124)
xgboost10
parallel10
python10
kubeflow10
hyperparameter-optimization10
scheduling10
deep-learning10
istio10
ray10
k8s10
optimization10
mesos10
linux10
llm-inference10
ai10
Programming languages (12)
Github contributions (5)
llm-d/llm-d-workload-variant-autoscaler
Jun 2025 - Jul 2026
Variant optimization autoscaler for distributed inference workloads
Contributions:214 reviews, 91 PRs, 96 pushes in 1 year
inference
IBMSpectrumComputing/ray-integration
Jun 2021 - Oct 2022
Ray with LSF. Users can start up a Ray cluster on LSF, and run DL workloads through that either in a batch or interactive mode.
Contributions:18 commits, 9 PRs, 16 pushes in 1 year 4 months
raystart-uphpc-applicationsbatchworkloads
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