AI / ML ENGINEER

Likith
Chilakalapadi Prabhu

Building reliable AI systems from retrieval to inference.

I design and build production-grade Generative AI, RAG, agentic workflows, LLM evaluation platforms, and scalable inference infrastructure.

Python · PyTorch · RAG · LangGraph · FastAPI · AWS · Kubernetes
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AGENT
RAG
LLM
EVAL
PRODUCTIONAI SYSTEMRELIABLE · SCALABLE
5+Years in AI / ML
34%Inference latency reduction
35K+Enterprise users supported
20+Evaluation configurations benchmarked

ABOUT

Engineering AI systems that work beyond the demo.

I focus on the full production AI lifecycle: retrieval, orchestration, model serving, evaluation, observability, and infrastructure.

My work centers on building AI systems that are not only accurate, but also measurable, scalable, reliable, and maintainable in real-world environments.

SELECTED WORK

Evaluation infrastructure for production LLM systems.

The flagship project focuses on quality regression detection, experiment tracking, concurrency, latency, and repeatable LLM evaluation.

FLAGSHIP PROJECT

EvalForge

LLM Evaluation & Regression Testing Platform

01

Automated evaluation platform for benchmarking model, prompt, and retrieval configurations across correctness, groundedness, citation accuracy, hallucination rate, latency, and cost.

01Test Dataset

Versioned evaluation cases and expected behavior.

→
02LLM Pipeline

Model, prompt, and retrieval configurations.

→
03Evaluation

Deterministic and LLM-as-a-judge scoring.

→
04Regression Gate

Blocks releases when quality thresholds fail.

93%intentional regressions detected
72%less manual evaluation effort
<250msP95 API latency
50+concurrent evaluation jobs
PythonFastAPIPyTorchMLflowPostgreSQLRedisAWS
LLM Evaluation Platform

EXPERIENCE

Production AI from models to infrastructure.

NVIDIAMar 2025 — Present

AI/ML Engineer

Production AI systems spanning multi-agent orchestration, enterprise RAG, distributed GPU inference, cloud-native deployment, LLMOps, and observability.

AccentureOct 2020 — Jul 2024

Machine Learning Engineer

Built AI/ML platforms involving RAG, scalable Python services, MLOps, event-driven data pipelines, cloud infrastructure, and enterprise integrations.

TECHNICAL STACK

Focused on the production AI lifecycle.

Generative AI & Agents

LLMs · Agentic AI · RAG · LangGraph · MCP · Tool Calling

ML & NLP

PyTorch · Hugging Face · NVIDIA NeMo · Embeddings · Reranking

Inference & Serving

TensorRT-LLM · Triton · vLLM · CUDA · FlashAttention

Backend & Data

FastAPI · gRPC · Kafka · Redis · PostgreSQL · Spark

Cloud & MLOps

AWS · Kubernetes · Docker · Terraform · MLflow · GitHub Actions

Evaluation & Reliability

LLM Evaluation · DeepEval · Observability · Guardrails · Tracing

EDUCATION

Master of Science in Computer Science

University at Buffalo, New York

Bachelor of Technology in Software Engineering

Vellore Institute of Technology

CERTIFICATIONS

  • NVIDIA Certified Associate — Generative AI LLMs
  • AWS Certified Machine Learning Engineer — Associate
  • Databricks Certified Generative AI Engineer Associate
  • Certified Kubernetes Administrator (CKA)

CONTACT

Interested in building production AI systems?

Open to AI/ML engineering opportunities and technically ambitious teams.

Email meLinkedIn