Rishabh Garg

Lead ML Engineer

San Francisco, California, United States6 yrs 6 mos experience

Highly StableAI Enabled

Key Highlights

Expert in Natural Language Processing and Deep Learning.
Experience with Blockchain platforms and DevOps pipelines.
Published research in ACL 2023 on ethical AI.

Stackforce AI infers this person is a Machine Learning Engineer specializing in Natural Language Processing and AI ethics.

Contact

Skills

Core Skills

Artificial Intelligence (ai)Machine LearningNatural Language Processing (nlp)

Other Skills

Trustworthy AIframeworksmodelsdatasetsScholarly Researchself rewarding LMsBioNLPNon Autoregressive Text generationresponsible AItoolchainsAI modelsMulti-Modal modelsAttention Manipulation frameworkdiscrete compression methodcontext window sizes

About

Research Engineer interested in Natural Language Processing . Experienced in Deep Learning Models for NLP and Vision ,developing Blockchain platforms and DevOps pipelines. Looking for Research Projects in natural language processing. Resume:- https://drive.google.com/file/d/1WNvg45p0jWH2CLduTFipVA1DJAE6Eg0j/view?usp=sharing

Experience

6 yrs 6 mos

Total Experience

2 yrs 7 mos

Average Tenure

1 yr 5 mos

Current Experience

Nvidia

2 roles

Senior ML engineer

Dec 2024 – Present · 1 yr 5 mos · Santa Clara County, California, United States

Working with Trustworthy AI team to create frameworks for aligning models and datasets along TAI principles

Trustworthy AIframeworksmodelsdatasetsArtificial Intelligence (AI)Machine Learning

Research Intern

Jun 2024 – Sep 2024 · 3 mos · Santa Clara, California, United States · On-site

Part of the responsible AI team, creating toolchains to assess AI models across modalities .
Created a Attention Manipulation framework for grounded explanations of Multi-Modal models like VILA on image and text outputs.

responsible AItoolchainsAI modelsMulti-Modal modelsAttention Manipulation frameworkArtificial Intelligence (AI)+1

University of massachusetts amherst

2 roles

Teaching Assistant

Sep 2024 – Dec 2024 · 3 mos · Amherst, Massachusetts, United States

Grader for COMPSCI 689:Advanced Machine Learning

Graduate Student Researcher

Jan 2024 – Jan 2025 · 1 yr · Amherst, Massachusetts, United States

1.Working on self rewarding LMs with BioNLP lab with Dr Hong Yu
2. IESL Lab: Non Autoregressive Text generation with Dr Andrew McCallum

Scholarly Researchself rewarding LMsBioNLPNon Autoregressive Text generationNatural Language Processing (NLP)Machine Learning

Cohere

Graduate Student Researcher

Feb 2024 – May 2024 · 3 mos · Remote

Worked on discrete compression method for LMs to enhance context window sizes , reducing inference cost and enabling longer documents to be processed, exploring different methods like RL and classification methods to create robust compressors

discrete compression methodcontext window sizesinference costlonger documentsRLclassification methods+2