Hi, I’m Shoa Aamir, a mid-senior ML engineer focused on building practical, scalable AI systems. I currently work with Function Health USA, where I forecast chronic-condition risks with ensemble models, design LLM workflows and AI Agents with tracing and evaluation, and fine-tune open-source LLMs on medical data to improve accuracy. I also build robust ETL pipelines for RAG workflows, construct knowledge graphs, and experiment with reinforcement learning, all while extending practical context windows and benchmarking prompt consistency. Beyond ML, I lead scalable filtering and GraphQL microservices architecture, and I’ve shipped backend and data engineering solutions across AWS, GCP, and serverless environments. I enjoy collaborating on cross-disciplinary teams, mentoring peers, and staying curious about Explainable AI and efficient inference techniques. I hold a BTech in Computer Science and Engineering from Lovely Professional University and have pursued certifications in ML from Stanford and German language proficiency from Goethe Institute.

Shoa Aamir

Hi, I’m Shoa Aamir, a mid-senior ML engineer focused on building practical, scalable AI systems. I currently work with Function Health USA, where I forecast chronic-condition risks with ensemble models, design LLM workflows and AI Agents with tracing and evaluation, and fine-tune open-source LLMs on medical data to improve accuracy. I also build robust ETL pipelines for RAG workflows, construct knowledge graphs, and experiment with reinforcement learning, all while extending practical context windows and benchmarking prompt consistency. Beyond ML, I lead scalable filtering and GraphQL microservices architecture, and I’ve shipped backend and data engineering solutions across AWS, GCP, and serverless environments. I enjoy collaborating on cross-disciplinary teams, mentoring peers, and staying curious about Explainable AI and efficient inference techniques. I hold a BTech in Computer Science and Engineering from Lovely Professional University and have pursued certifications in ML from Stanford and German language proficiency from Goethe Institute.

Available to hire

Hi, I’m Shoa Aamir, a mid-senior ML engineer focused on building practical, scalable AI systems. I currently work with Function Health USA, where I forecast chronic-condition risks with ensemble models, design LLM workflows and AI Agents with tracing and evaluation, and fine-tune open-source LLMs on medical data to improve accuracy. I also build robust ETL pipelines for RAG workflows, construct knowledge graphs, and experiment with reinforcement learning, all while extending practical context windows and benchmarking prompt consistency.

Beyond ML, I lead scalable filtering and GraphQL microservices architecture, and I’ve shipped backend and data engineering solutions across AWS, GCP, and serverless environments. I enjoy collaborating on cross-disciplinary teams, mentoring peers, and staying curious about Explainable AI and efficient inference techniques. I hold a BTech in Computer Science and Engineering from Lovely Professional University and have pursued certifications in ML from Stanford and German language proficiency from Goethe Institute.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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Language

English
Fluent
German
Advanced

Work Experience

Backend Engineer at Everyday Speech USA
November 1, 2023 - November 1, 2023
Designed and developed serverless, event-driven video processing pipelines on AWS; built purchase operations automation microservices in domain-driven architecture using NestJS on AWS; streamlined data integration using anti-corruption layers for HubSpot and Chargify; implemented CI/CD pipelines with GitHub Actions for automated tests and AWS deployments.
Mid-Senior Machine Learning Engineer at Function Health USA
November 1, 2023 - November 14, 2025
Leading predictive risk forecasting for chronic conditions using ensemble modeling; architecting and contributing to building LLM workflows and AI Agents with tracing and evals; fine-tuning open-source LLMs and embedding models on unstructured and structured medical data to boost accuracy; engineering robust ETL pipelines to support RAG workflows, knowledge graph construction, fine-tuning and reinforcement learning; researching and optimizing RAG with KV-Cache techniques and attention mechanisms for significant efficiency gains; extending the practical context window of a locally hosted LLM from 15K to 65K tokens; designing benchmarks for prompt consistency and accuracy; contributing to Explainable AI techniques on causal RAGs; leading scalable Filtering Operations architecture for GraphQL microservices across the company.
Software Development Engineer Intern at Amazon.com Hyderabad
August 1, 2022 - August 1, 2022
Designed and developed an AWS SQS-invoked Lambda to ingest return creation events; crafted distributed architecture to transform containerization events into tracking events; contributed to the ideation and development recognized as an Amazon Ideathon Winner.
Remote Machine Learning Engineer at RC3 Canada Inc.
May 1, 2022 - May 1, 2022
Developed REST APIs and sockets to productionize deep learning models; trained models to determine pace and posture from live workout streams; reduced latency by introducing Redis caching; built and scaled an intelligent chatbot with RASA and an NLP analytics pipeline for NUI experiences.

Education

Bachelor of Technology in Computer Science and Engineering at Lovely Professional University
January 11, 2030 - November 14, 2025

Qualifications

Machine Learning
September 1, 2021 - November 14, 2025
B2 German
January 1, 2019 - November 14, 2025

Industry Experience

Computers & Electronics, Software & Internet, Healthcare, Education, Media & Entertainment