Open to opportunities

Bruce Wayne

@brucewayne

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Machine learning engineer specializing in distributed training and scalable AI systems.

India

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What I'm looking for

I seek roles building scalable ML infrastructure and distributed training systems where I can improve performance, automate deployments, and work on production-ready AI platforms within collaborative teams.

I am a machine learning engineer focused on distributed training frameworks and scalable AI systems, with hands-on experience building TensorFlow distributed training pipelines and on-premise high-performance Spark clusters. I have delivered performance improvements such as a 4.5x speedup on 4 GPUs and automated cluster deployment that reduced setup time by 92%.

My work spans designing custom training loops with GradientTape and AutoGraph, implementing distributed metric collection to maximize GPU utilization, and building production-ready retrieval and RAG pipelines for intelligent shopping assistants using FAISS, LangGraph, and SentenceTransformers. I prioritize reproducibility, modular architecture, and maintainable code to accelerate iteration and deployment.

Experience

Work history, roles, and key accomplishments

Current

Research Intern

Current

UbiSense Labs

Aug 2025 - Present (8 months)

Designed custom TensorFlow training loops using GradientTape and AutoGraph to speed execution and implemented a distributed training framework that achieved 4.5x speed on 4 GPUs while enabling 85–95% GPU utilization and reproducible metrics collection.

Autograph TensorFlow Distributed Training GradientTape AutoGraph Distributed Systems Python

Education

Degrees, certifications, and relevant coursework

Dhirubhai Ambani Institute of Information and Communication Technology

Bachelor of Technology (Honours), Information & Communication Technology

Grade: 7.97 / 10

B.Tech. (Honours) in Information & Communication Technology with a minor in Computational Science; graduated May 2025 with a cumulative GPA of 7.97/10.