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I am an innovative and results-driven AI/ML Engineer with over 9 years of experience in building production-grade machine learning systems, large-scale recommendation engines, and generative AI solutions. I've worked at leading companies like Meta, Amazon, and AWS, focusing on areas such as LLMs, NLP, recommender systems, and distributed backend engineering. Currently, I lead initiatives to improve search relevance at Meta, integrating LLM-based evaluation pipelines and optimizing search infrastructure. I am passionate about technical leadership, mentoring, and collaborating across engineering, product, and data science teams to deliver impactful AI products at scale.…I am an innovative and results-driven AI/ML Engineer with over 9 years of experience in building production-grade machine learning systems, large-scale recommendation engines, and generative AI solutions. I've worked at leading companies like Meta, Amazon, and AWS, focusing on areas such as LLMs, NLP, recommender systems, and distributed backend engineering. Currently, I lead initiatives to improve search relevance at Meta, integrating LLM-based evaluation pipelines and optimizing search infrastructure. I am passionate about technical leadership, mentoring, and collaborating across engineering, product, and data science teams to deliver impactful AI products at scale.

Rakshesh Rajeshkumar Shah

AI Engineer, Data Scientist, Game Developer, +3

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I am an innovative and results-driven AI/ML Engineer with over 9 years of experience in building production-grade machine learning systems, large-scale recommendation engines, and generative AI solutions. I've worked at leading companies like Meta, Amazon, and AWS, focusing on areas such as LLMs, NLP, recommender systems, and distributed backend engineering. Currently, I lead initiatives to improve search relevance at Meta, integrating LLM-based evaluation pipelines and optimizing search infrastructure. I am passionate about technical leadership, mentoring, and collaborating across engineering, product, and data science teams to deliver impactful AI products at scale.…I am an innovative and results-driven AI/ML Engineer with over 9 years of experience in building production-grade machine learning systems, large-scale recommendation engines, and generative AI solutions. I've worked at leading companies like Meta, Amazon, and AWS, focusing on areas such as LLMs, NLP, recommender systems, and distributed backend engineering. Currently, I lead initiatives to improve search relevance at Meta, integrating LLM-based evaluation pipelines and optimizing search infrastructure. I am passionate about technical leadership, mentoring, and collaborating across engineering, product, and data science teams to deliver impactful AI products at scale.

Available to hire

I am an innovative and results-driven AI/ML Engineer with over 9 years of experience in building production-grade machine learning systems, large-scale recommendation engines, and generative AI solutions. I’ve worked at leading companies like Meta, Amazon, and AWS, focusing on areas such as LLMs, NLP, recommender systems, and distributed backend engineering.

Currently, I lead initiatives to improve search relevance at Meta, integrating LLM-based evaluation pipelines and optimizing search infrastructure. I am passionate about technical leadership, mentoring, and collaborating across engineering, product, and data science teams to deliver impactful AI products at scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

Javanese

Advanced

Work Experience

Software Engineer at Meta

June 1, 2024 - Present

Spearheading core initiatives to improve Facebook’s entity search relevance with LLM-based zero/few-shot scoring and human-in-the-loop validation. Designed a code-review-time test automation framework reducing SEVs and improving code health. Enhanced computational efficiency via intent-driven query optimization, reducing GPU/CPU usage and service latency. Collaborated with cross-functional teams to optimize retrieval, fine-tune ranking models, and implement semantic search techniques. Mentored engineers on scalable ML system design and LLMOps, while driving AI strategy for low-latency, large-scale systems supporting billions of users.

Software Engineer at Amazon

June 30, 2024 - July 18, 2025

Led design and development of latency-sensitive, scalable, distributed backend recommendation engine powering personalized suggestions across Amazon. Built infrastructure supporting end-to-end ML workflows including training, evaluation, and real-time inference. Explored LLM-based solutions for customer experience and personalization specifically in Amazon Beauty and related verticals. Improved reliability, observability, and testing frameworks. Collaborated cross-functionally for roadmap and experimentation, while mentoring engineers and improving team processes.

Software Engineer at Amazon Web Services (AWS)

April 1, 2022 - July 18, 2025

Early engineer behind AWS services such as DeepComposer, BugBust, and DeepRacer Student, delivering production-grade ML and generative AI solutions. Developed core ML pipelines for music creation and gamified bug-fixing competitions including leaderboard systems. Built course tracking and quiz infrastructure for AI/ML education. Worked across backend, ML pipeline orchestration, distributed systems, and system monitoring while collaborating with multiple teams to deliver scalable global services.

Software Engineer at Asurion

November 1, 2019 - July 18, 2025

Developed AI-powered chatbot automating mobile insurance claims, architected serverless backend infrastructure using AWS Lambda and API Gateway. Designed and implemented deep learning pipelines spanning data collection to model deployment. Built and fine-tuned NLP models including intent classification, named entity recognition, sentiment analysis using traditional and advanced deep learning architectures such as BERT and custom attention models. Collaborated cross-functionally to align ML with business needs and ensured production-grade robustness.

Software Engineer at Meta

June 1, 2024 - Present

Spearheaded core initiatives to improve Facebook’s entity search relevance, architected a code-review-time test automation framework to reduce SEVs and enhance code health, designed and deployed advanced LLM-based evaluation pipelines, optimized computational efficiency with intent-driven query optimization, collaborated across product and research teams to innovate semantic search techniques, contributed to LLM-integrated search workflows including RAG and embedding-based search, mentored engineers on scalable ML system design and LLMOps, and drove Meta’s broader AI strategy aligning research with production-grade implementation.

Software Engineer at Amazon

June 30, 2024 - July 18, 2025

Led design and development of a latency-sensitive, scalable backend recommendation engine powering personalized suggestions on various Amazon pages. Built and maintained infrastructure for end-to-end ML workflows, prototyped LLM-based solutions for customer experience, improved infrastructure reliability and observability, collaborated cross-functionally to drive experimentation and product impact, mentored engineers, and contributed to adoption of distributed systems best practices and MLOps automation.

Software Engineer at Amazon Web Services (AWS)

April 30, 2022 - July 18, 2025

Early engineer behind AWS services such as DeepComposer, BugBust, and DeepRacer Student delivering ML and Generative AI solutions. Built training and inference pipelines for music creation, developed real-time multi-tenant leaderboard systems for bug-fixing competitions, created course tracking infrastructure for AI/ML education, contributed across backend services and ML pipeline orchestration, and collaborated with cross-functional teams to deliver scalable services globally.

Software Engineer at Asurion

November 1, 2019 - July 18, 2025

Key developer for AI-powered chatbot automating mobile insurance claims, architected serverless backend infrastructure using AWS Lambda and API Gateway, designed and implemented deep learning pipelines including data collection and model training, developed and fine-tuned NLP models for intent classification, NER, and sentiment analysis using a variety of NLP techniques and models, collaborated cross-functionally to align ML solutions with business needs, and ensured production-grade chatbot system performance.