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Aman Singh

AI/ML Engineer | NLP & Generative AI | RAG Pipelines | MLOps | Azure | Python

Mumbai

4+ years of work experience

HTC Global Services
Mar 20242 yrs 4 mosPresent

• Led applied research and experimentation with LLMs and generative AI architectures (Transformers, RAG); evaluated state-of-the-art models on Hugging Face and Azure OpenAI for production suitability. • Designed and implemented scalable ML pipelines using PyTorch, TensorFlow, and Hugging Face Transformers; integrated MLflow for experiment tracking, model versioning, and performance monitoring. • Architected end-to-end AI/ML systems covering data ingestion, model training, inference, and feedback loops; deployed models into production via Azure DevOps CI/CD with automated regression validation. • Built LLM output validation and RAG pipeline testing frameworks evaluating hallucination, context fidelity, schema compliance, and latency SLAs across model API versions. • Collaborated with data scientists, software engineers, and business stakeholders to align AI/ML capabilities with health-tech goals; authored internal whitepapers on generative AI evaluation methodologies. • Implemented data drift detection, Great Expectations integrity checks, and A/B/shadow testing frameworks; monitored production model accuracy and recommended retraining triggers based on drift metrics.
Mphasis
Oct 20234 mosJan 2024

• Automated ML model validation and regression API testing using Python and REST Assured; ensured test coverage aligned with business acceptance criteria in Agile sprints. • Collaborated with data engineers and developers to validate ML pipeline outputs, track defects in JIRA, and maintain traceability across cross-functional services.
Unosis IT Solutions Pvt. Ltd.
Oct 20211 yr 10 mosJul 2023

• Built Selenium + Python automation suites and REST API test collections; validated application data using SQL queries across integration and system-level test scenarios. • Supported automation initiatives reducing manual regression effort, documented test plans, and contributed to CI/CD pipeline testing integration.

Education

Noida Institute of Engineering & Technology

Bachelor of Technology, Information Technology

Noida Institute of Engineering & Technology

20184 yrs2022
Udaya Public School

CBSE XII

Udaya Public School

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Headline

AI/ML Engineer | NLP & Generative AI | RAG Pipelines | MLOps | Azure | Python

About

AI/ML Engineer with 3+ years building production-grade machine learning and NLP systems in health-tech. I specialize in LLM evaluation, RAG pipeline design, and MLOps on Azure translating complex business problems into scalable, deployable AI solutions. What I've delivered: Benchmarked 10+ LLM architectures, cutting model selection time by ~40% Built RAG validation frameworks that reduced undetected production errors by 35% Maintained 92%+ model accuracy in production through automated drift detection and retraining pipelines Authored internal whitepapers on generative AI evaluation adopted across health-tech teams Mentored junior engineers, reducing onboarding time by ~30% Technical focus: Python · PyTorch · TensorFlow · Hugging Face · LangChain · MLflow · Azure OpenAI · Scikit-learn · RAG · LLM Fine-Tuning Open to roles in applied AI/ML, generative AI systems, and MLOps engineering.

Location

Mumbai

Work experience

Associate Software Engineer at HTC Global Services, Mar 2024 - Present · 2 yrs 4 mos, • Led applied research and experimentation with LLMs and generative AI architectures (Transformers, RAG); evaluated state-of-the-art models on Hugging Face and Azure OpenAI for production suitability. • Designed and implemented scalable ML pipelines using PyTorch, TensorFlow, and Hugging Face Transformers; integrated MLflow for experiment tracking, model versioning, and performance monitoring. • Architected end-to-end AI/ML systems covering data ingestion, model training, inference, and feedback loops; deployed models into production via Azure DevOps CI/CD with automated regression validation. • Built LLM output validation and RAG pipeline testing frameworks evaluating hallucination, context fidelity, schema compliance, and latency SLAs across model API versions. • Collaborated with data scientists, software engineers, and business stakeholders to align AI/ML capabilities with health-tech goals; authored internal whitepapers on generative AI evaluation methodologies. • Implemented data drift detection, Great Expectations integrity checks, and A/B/shadow testing frameworks; monitored production model accuracy and recommended retraining triggers based on drift metrics.

Associate Software Engineer at Mphasis, Oct 2023 - Jan 2024 · 4 mos, • Automated ML model validation and regression API testing using Python and REST Assured; ensured test coverage aligned with business acceptance criteria in Agile sprints. • Collaborated with data engineers and developers to validate ML pipeline outputs, track defects in JIRA, and maintain traceability across cross-functional services.

Associate Software Engineer at Unosis IT Solutions Pvt. Ltd., Oct 2021 - Jul 2023 · 1 yr 10 mos, • Built Selenium + Python automation suites and REST API test collections; validated application data using SQL queries across integration and system-level test scenarios. • Supported automation initiatives reducing manual regression effort, documented test plans, and contributed to CI/CD pipeline testing integration.

Education

Bachelor of Technology, Information Technology, Noida Institute of Engineering & Technology

CBSE XII, Udaya Public School