Rishika Agarwal

Machine Learning Engineer

United States11 yrs experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in developing on-device NLP models.
Experience in generative AI for health applications.
Strong background in machine learning and computer vision.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in NLP and generative AI solutions.

Contact

Skills

Core Skills

Machine LearningNatural Language ProcessingGenerative AiComputer Vision

Other Skills

Agentic AIAlgorithmsApplication Programming Interfaces (API)Architectural DesignCC++Data EngineeringData MiningData StructuresDigital ElectronicsEdge ComputingElectrical EngineeringFine-tuning LLMGNU OctaveInternationalization

About

Machine Learning Engineer at Apple, working on developing and deploying light and performant NLP models on-device, for powering free-form natural language search on various search platforms. I also work with language engineers to understand peculiarities of different languages, to build multi-lingual models which serve our global users.

Experience

11 yrs

Total Experience

3 yrs 6 mos

Average Tenure

5 mos

Current Experience

Google

Senior Machine Learning Engineer

Jan 2026 – Present · 5 mos · Mountain View, California, United States · Hybrid

Understanding users' life through their photos, to power Personal Intelligence in Gemini, Ask Photos, and other forward-looking personalization features.

MLOpsLLM evaluationFine-tuning LLMAgentic AIRetrieval-Augmented Generation (RAG)Time Series Forecasting+25

Apple

3 roles

ML Research Engineer, Health

Mar 2025 – Jan 2026 · 10 mos

Generative AI solutions for personalized health and fitness features - developed a multi-agent framework and designed evaluation strategy in collaboration with clinical and product teams.

Fine-tuning LLMRetrieval-Augmented Generation (RAG)Agentic AILLM evaluationSynthetic Data GenerationMLOps+2

Senior Machine Learning Engineer

Promoted

Jan 2021 – Mar 2025 · 4 yrs 2 mos

Developed light and performant on-device models for Natural Language Understanding powering various Search platforms (Spotlight, Photos, Messages, Image Playground), and expanded the model to 15+ international locales.

Large Language Models (LLM)Edge ComputingSynthetic Data GenerationInternationalizationData EngineeringPyTorch+2

Machine Learning Engineer

Aug 2019 – Jan 2021 · 1 yr 5 mos

AIML Rotation Program : worked on research and development projects with multiple teams in AI/ML org. Some teams I worked with : ASR, Visual Intelligence, Swift, Biosignals Investigation Group.
Siri : Expanded Query Understanding model to new domains.

Computer VisionModel CompressionPyTorchTensorFlowApplication Programming Interfaces (API)Machine Learning

University of illinois at urbana-champaign

3 roles

Graduate Teaching Assistant

Aug 2018 – May 2019 · 9 mos · Urbana-Champaign, Illinois Area

TA for CS105 - Computer Science for Non Engineering Majors

Graduate Researcher, Adversarial Machine Learning

Oct 2017 – May 2019 · 1 yr 7 mos · Urbana-Champaign, Illinois Area

Research student with Prof. Sanmi Koyejo, studying novel techniques of adversarial attacks and defenses for generative deep learning models

Graduate Teaching Assistant

Aug 2017 – May 2018 · 9 mos · Urbana-Champaign, Illinois Area

TA for CS125 (An Introduction to Computer Science)
Hold lab discussion hour for four hours every week, where I review the concepts discussed in the lectures, and help the students complete some programming exercises in Java.
Design lab handouts and programming problems for the course

Meta facebook

Data Science Intern

May 2018 – Aug 2018 · 3 mos · Menlo Park

Samsung r&d institute india

Research Intern

May 2016 – Jul 2016 · 2 mos · Bangalore

Worked on developing the PHY layer of 5G Communication Systems.

Indian institute of technology, kanpur

4 roles

Academic Mentor

Jul 2014 – Jul 2015 · 1 yr

Mentored freshmen in 2 courses : Fundamentals of Computing and Introduction to Electrodynamics.

Student Guide

Jul 2014 – Jul 2015 · 1 yr

Institute Captain - Lawn Tennis

Feb 2014 – Feb 2015 · 1 yr

Research intern

Jan 2013 – Jan 2014 · 1 yr

Proposed a novel method for binaural source localization using a HRTF data model with enhanced frequency diversity.
Co-authored a paper to be published in EUSIPCO conference 2016, in Budapest, Hungary.