Saloni Garg

01Experience

• Jan 2025 to present

  Staff Machine Learning Engineer, Adobe

  Firefly, San Jose, CA. Tech Lead for post-training multimodal LLM optimizations.

  - Lead post-training infrastructure for LLMs and diffusion models (PyTorch, CUDA, FSDP, NCCL), enabling fast iteration on quality and alignment.

  - Own end-to-end RLHF pipelines (reward models, preference data, policy optimization) for production LLM alignment; implemented SFT and preference-based optimization (DPO) pipelines.

  - Technical lead for distillation of diffusion models for video generation, editing, and propagation-based editing. Distilled models are live in production, preserving 98%+ teacher model quality in internal human-preference evaluations while reducing sampling steps from 50 to 4-8.

  - Developed high-throughput GPU training pipelines with mixed precision (FP16/BF16), gradient checkpointing, and optimized dataloaders; reduced training time by 2.2x for Firefly video generation.

  - Led a team of 6 ML engineers on generative models and large-scale distributed training.

• Jan 2023 to Jan 2025

  Senior Machine Learning Engineer, Wayfair

  San Francisco Bay Area. Designed and developed a visual product search system using deep image embeddings to retrieve visually similar furniture products across 30M+ catalog images. Built multimodal retrieval models combining product images, titles, descriptions, and catalog attributes for search and recommendation candidate generation.

• Oct 2020 to Dec 2022

  Machine Learning Engineer, Wayfair

  Berlin, Germany. Developed image-text matching models aligning customer queries with product imagery; built pipelines to extract product attributes (color, material, style, shape, room placement) from product images; developed computer vision classifiers across 3k+ furniture categories; created large-scale multimodal datasets from product images, descriptions, taxonomy labels, reviews, and interaction data.

• Jul 2020 to Oct 2020

  Data Scientist, The Linux Foundation

• Education

  B.Tech, Computer Science and Engineering, LNMIIT Jaipur

  The LNM Institute of Information Technology, Jaipur, India.

02Selected work

• 2026

  gpu-train-debug

  RL environment for diagnosing GPU training failures, in Prime Intellect Verifiers format. Published on the Prime Intellect Hub and as a dataset on Hugging Face, with train, hard, test, and out-of-distribution splits and a full validation run on A100 hardware.

  Python / Verifiers / Prime Intellect / Hugging Face

• 2026

  OpenEnv, verifier fix (PR 1477)

  Contribution to OpenEnv: code verifiers no longer pass on an untouched database. Marked ready for review, with the environment test suite passing.

  Python / RL environments / open source contribution

• 2026

  memfix

  Provenance-first, correctable memory layer for AI agents: source pointers, append-only log, tombstones, and an MCP server. Published under MIT; listed on Glama.

  Python / MCP / SQLite or Postgres / MIT

• 2026

  jev-max

  Browser agent for general web tasks: shadow DOM and iframe handling, canvas vision fallback, uploads, drag and drop, multi-tab support, MCP server, and a benchmark suite. Published under MIT.

  TypeScript / Playwright / MCP / MIT

• Ongoing

  Open source

  Contributor to Ray and PyTorch. Full list of repositories at github.com/saloni-garg.

03Publications and IP

• Book: Retrieval-Augmented Generation (RAG) for Enhancing AI Applications. De Gruyter, 2026. Publisher page via the book link.
• Patent: A System and Method for Automated Drift Detection and Model Retraining in Machine Learning Pipelines. Indian Patent Office, 2025.
• Patent: AI and Computer Vision-Based Animal Surveillance System. Indian Patent Office, 2024.
• Unsolvability Ceiling in Multi-LLM Routing: An Empirical Study of Evaluation Artifacts. arXiv.
• ECG-Lense: Benchmarking ML and DL Models on PTB-XL Dataset. IEEE, 2024.
• Climate Change Analytics Using AI. IEEE ETNCC, 2024.
• Further papers: Production-Grade Retrieval-Augmented Generation: Architecture, Failure Modes, and Optimization at Scale; Cost-Efficient Large Language Model Serving Through Adaptive Inference and Resource-Aware Scheduling; Designing Scalable Agentic Retrieval Systems for Autonomous Decision-Making Under Real-World Constraints; Inference-First Architectures for Large Language Models in Cloud-Native Environments.

04Talks

• 2026

  AI Risk Summit. KV-Cache as Attack Surface: Side Channels in Shared LLM Inference Infrastructure.

• 2026

  CloudX. Token Spikes, Timeout Cascades, and Silent Failures: Debugging GenAI Systems in Production.

• 2025

  Vector Search Conference. GPU or CPU? Optimizing Vector Search Infrastructure for Cost and Speed.

• 2025

  CloudX. How to Build a Blameless Debugging Culture with Observability Tools.

• 2024

  NDC London. Neural Style Transfer: The Art and Science of Generative AI.

• 2023

  BuildStuff, Vilnius. Can You Guess Which Song Snippets Are Written by AI?

• 2023

  CloudX PRO. Serverless: Because Managing Servers Is So 2022.

• 2019

  Red Hat Summit, Boston. Women in Open Source Award segment, and an interview on theCUBE.

• 2019

  Linux App Summit, Barcelona. Lightning talk, "Open Source is great, how can we spread it?", with Amit Sagtani; filmed interview with Nextcloud founder Frank Karlitschek.

• 2019

  UseData Conf, Moscow. Machine Learning Based Autonomous Car Driving Algorithms.

• Also

  PyCon; ILP Summit. Tech speaker.

05Awards and recognition

• EDGE in Tech Athena Award, 2026. UC Berkeley (CITRIS and the Banatao Institute).
• Adobe Employee Spot Bonus, 2026.
• AI and Data Science Leader of the Year, 2025. WomenTech Global Awards.
• AI for Good Impact Award, 2025.
• International Women in Open Source Award, 2019. Red Hat, Boston.
• Google Venkat Panchapakesan Memorial Scholar. Selected top 6 from 1000+ applicants.
• Silicon Valley Fellowship. Top 100 out of 20,000 applicants.
• Mozilla Open Leader, 2019.

06Contact

LinkedIn: linkedin.com/in/saloni-garg
Google Scholar: Google Scholar profile
GitHub: github.com/saloni-garg

Email salonigarg2318@gmail.com