Balaji Subramaniam
Engineering Manager at Google
Greater Seattle Area United States
Summary
🤩
Rockstar🎓
Top SchoolBalaji Subramaniam is an Engineering Manager at Google with a decade of experience building and operating cloud-native and ML infrastructure. He brings deep hands-on expertise in Kubernetes, DevOps, and distributed systems—demonstrated by contributions to node-feature-discovery (adding RDT detection and node labeling) and IntelLabs’ Coach (Kubernetes orchestration and S3/NFS backends for RL workloads). A PhD-trained computer scientist from Virginia Tech, he blends research rigor with practical engineering, often focusing on making complex platform capabilities production-ready. Based in the Greater Seattle Area, he excels at translating low-level resource discovery and orchestration challenges into reliable team-delivered solutions.
10 years of coding experience
PhD, Computer Science, PhD, Computer Science at Virginia TechAnna University, Chennai
Github Skills (23)
kubernetes10
docker10
python10
scripting10
rda10
dockers10
data-storage10
script10
go10
amazon-s310
kubernetes-pods10
rd10
aws-s310
sh10
cpuid10
Programming languages (10)
Github contributions (5)
kubernetes-sigs/node-feature-discovery
Jul 2016 - Apr 2018
Node feature discovery for Kubernetes
Role in this project:
DevOps Engineer
DevOps EngineerContributions:22 commits, 49 PRs, 19 pushes in 1 year 9 months
Contributions summary:Balaji primarily focused on enhancing the node feature discovery process within a Kubernetes environment. Their contributions involved enabling RDT (Resource Director Technology) discovery and integrating it into the node labeling system. This included modifying the main application and creating scripts to detect and label nodes based on CPU features and RDT capabilities. Furthermore, they added demo scripts and templates to streamline the testing and demonstration of these features.
feature-detectionk8s-sig-nodefeature-discoveryrdtdiscovery
IntelLabs/coach
Oct 2018 - Nov 2018
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Role in this project:Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:11 commits, 4 PRs, 4 pushes in 1 month
Contributions summary:Balaji contributed significantly to the development of data store backends, adding NFS and S3 implementations for data storage within the reinforcement learning environment. They integrated Kubernetes orchestration for these data stores. The commits also reflect the setup and integration of distributed Coach functionalities, including the configuration and deployment of trainers and rollout workers using Kubernetes. Furthermore, they refactored the code by making improvements on save checkpoint secs arg in distributed Coach and also updated the way how to handle both Environment Steps and Episodes on the subscriber side.
starcraftstate-of-the-artdeep-reinforcement-learningstarcraft2carla
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