ML Engineer at Google, working on Keras — I enjoy making machines a little smarter every day, and making the smart ones run fast on small devices. Previously at Qualcomm and Samsung R&D, building face recognition, computer vision, and sensor-driven systems for millions of devices. Based in India 🇮🇳.
🌐 pctablet505.github.io · 💼 LinkedIn · 📈 1,000+ contributions in the last year
108 PRs authored across Google's Keras ecosystem — 43 merged (keras 26 · keras-hub 17) and 35 in review across keras, keras-hub, keras-io & litert-torch.
Merged work I'm proud of:
- keras#22758 — LiteRT export for the PyTorch backend: on-device deployment of PyTorch-trained Keras 3 models
- keras-hub#2132 — Llama 3.1 implemented in KerasHub
- keras#22362 — serialization fix: custom models with sublayers in nested lists failed to save/load
- keras#22998 — torch-backend
SymInthandling inconvert_to_tensorandslice
In review right now: a 13-PR torch-performance series (SDPA causal dispatch,
convert_to_tensor fast paths, …), KerasHub → LiteRT-LM export, and the
official keras.io LiteRT export guide —
open PRs →
flowchart LR
A["Frontier model<br/>(Gemma, …)"] --> B["Keras 3<br/>multi-backend"]
B --> C["LiteRT / LiteRT-LM<br/>quantize + export"]
C --> D["📱 On-device<br/>fast · private · offline"]
Edge & on-device AI · model optimization (quantization, latency, memory) · multi-backend Keras internals · computer vision & applied ML that actually ships.
Outside of Keras, my main project is RL Alpha Labs — a JAX-native algorithmic-trading platform: PPO/DQN agents trading across 746 NSE instruments on 3.5+ years of market data, 128 vectorized environments for parallel rollout, and full portfolio simulation with risk controls. The code is private, but there's a live demo →
🕶 The part you can't see here: my major work before Google was face recognition and face-related solutions — plus computer-vision and camera/sensor problems — at Samsung R&D and Qualcomm. Real-time face auth serving 10,000+ registered faces on-device, embedding search cut from 1,200 ms → 87 ms, sensor-based drop detection at 95% less power. All closed-source, so GitHub only shows my Keras side.
| Project | What it is |
|---|---|
| RL Alpha Labs 🔒 | JAX-native RL trading platform — PPO/DQN over 746 NSE instruments, 128 vectorized envs, portfolio simulation with risk controls · private repo, live demo |
| ats-optimizer | Truthful, human-in-the-loop job-application automation — feed-based discovery, knowledge vault, tailored resumes, ATS analysis |
| litert-demo | End-to-end export of KerasHub Gemma3 → LiteRT .tflite / LiteRT-LM .litertlm |
| gemma-tflite-android-demo | Gemma running fully on-device on Android |
| jax-windows-cuda-build | CUDA build scripts, patches & pre-built JAX wheels for Windows |
| daily_tracker | Cross-platform daily task tracker with Google Drive sync & auto-updates |
| ML-Guide | Curated AI/ML learning path — courses, books, study notes |
- Better performance from smaller models — quantization, distillation, smarter kernels
- Synthetic data generation techniques
- Building a gallery search system