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Skanda Vyas Srinivasan
Intern Software Engineer specializing in full-stack, ML, and optimization
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Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.
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Key Strengths
- Built a PyTorch LSTM MIDI music-generation system and improved coherence with Bahdanau attention
- Applies research papers to solve modeling limitations (long-range dependency capture)
- Uses mixed-method evaluation: training loss/convergence plus structured qualitative listening tests
- Designs AI agents with explicit success criteria, modular workflows, and early guardrails
- Practical distributed/parallel ML experience with Ray (hyperparameter tuning, multi-GPU workloads) and awareness of GPU scheduling/memory pitfalls
- Hands-on containerized development using Docker Compose for multi-service backend setups
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Experience
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3 publications
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