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Karthik Raja Anandan
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Karthik Raja Anandan

AI / ML Engineer

Production AI agents, evals, multi-agent systems. Founding engineer; open-source Google Tunix, LangChain, Ivy. NVIDIA GTC 2026 · SemEval 2025 Task 4 Winner. M.S. AI @ UC Santa Cruz (3.9).

Pleasanton, CA kanandan@ucsc.edu

M.S. in Artificial Intelligence

University of California, Santa Cruz

Sep 2024 - Dec 2025 GPA: 3.9/4.0

B.E. in Computer Science

SSN College of Engineering

Aug 2019 - Aug 2023 GPA: 3.9/4.0

AI/ML Engineer (Founding Engineer)

Elas

Jan 2026 - Present Pleasanton, CA
Built 160-scenario eval framework with golden replay harness for agentic correctness (routing, tool selection, code gen)
Designed routing across 10+ specialized agents with quality gates and regression feedback before deploy
Authored 168-page developer docs and automated release pipelines for the agent platform
Multi-AgentAgent EvalsGolden ReplayMCPArgo CI/CD

AI Research Engineer

Samsung Research Capstone

Sep 2025 - Dec 2025 Santa Cruz, CA
Autonomous GUI agent with event capture/replay to verify long-horizon agentic workflows
Validated 1.5-bit quantized 32B Qwen on 2x RTX 3070 with systematic regression testing
Built validation pipelines checking tool selection, scheduling, and task completion
GUI AgentsQuantizationQwenvLLMAgent Evals

Software Development Engineer

Citi Corp

Aug 2023 - Sep 2024 Chennai, India
Automated data validation pipelines (Hadoop, Spark) — 25% faster processing
Event-driven services processing millions of events daily
HadoopSparkData PipelinesKafka

NLP Engineering Intern

MultiOn (Stanford Startup)

Jun 2023 - Aug 2023 Palo Alto, CA
Merged LangChain PR #12392; +40% agentic accuracy with retrieval + vector DBs
Open source: Tunix #1552, Ivy #13280 (merged)
LangChainRAGVector SearchOpen Source
SemEval 2025 Task 4 Winner - Best Paper Award

Graduate Researcher

Chenguang Wang's Lab — UC Santa Cruz

Multi-Agent Interpretability, Agentic ML

Sep 2024 - Dec 2025 Santa Cruz, CA
Contributing to Google Tunix (PR #1552), Ivy (merged), massgen, and rllm
Collaboration with AutoGen creator Chi Wang (DeepMind) on consensus-based multi-agent frameworks
SemEval 2025 Task 4 Winner — Best Paper Award (hallucination detection); 4 published ML papers
Multi-Agent SystemsInterpretabilityGoogle TunixPyTorchmassgenrllm

Research Assistant

HPC Lab — Anna University (SSNCE)

Multimodal ML, Robotics

May 2021 - Sep 2023 Chennai, India
Built CLIP-based multimodal routing with automated validation (0.90 confidence)
Designed 6-DOF robotic arm with test-driven optimization (73% accuracy)
Published benchmark on HuggingFace; multiple ML papers (FIRE, journals)
CLIPPyTorchRoboticsHuggingFaceXGBoost

LLM Evaluation Framework

Built automated eval pipeline for RAG systems measuring faithfulness, relevance, and hallucination rate across model versions; supports regression detection and multi-model comparison.

PythonPyTorchRAGLLMEvaluation

AI Agent Framework

End-to-end agentic framework with SQS-backed task pipelines, Hybrid RAG with pgvector, MCP tool orchestration, and comprehensive agent evaluation suite.

PythonAI AgentsRAGMCPProduction ML

Multimodal RAG System

Advanced retrieval-augmented generation system combining text, image, and audio modalities for enhanced knowledge retrieval.

Multimodal AIRAGKnowledge RetrievalPythonPyTorch
Ai And Ml LLMs · Multi-Agent Orchestration · Agent Evals · RAG · PyTorch · vLLM · GRPO · DDP · Quantization · NLP
Testing And Validation Eval Pipelines · DeepEval · Golden Replay · Integration Testing · Regression Testing · Langfuse
Languages Python · C++ · Go · SQL · Bash
Tools And Infra LangChain · MCP Servers · HuggingFace · Docker · Kubernetes · AWS (ECS, SQS)

A Novel Dataset for Fake News in Tamil

Karthik Raja Anandan, et al. — SPELLL 2022 (2022)

Abusive and Threatening Language Detection in Native Urdu Tweets

Karthik Raja Anandan, et al. — FIRE 2021 (2021)

Detecting Malicious IoT Traffic Using Machine Learning Techniques

Karthik Raja Anandan, et al. — Romanian Journal of Information Technology and Automatic Control (2023)

LeSS Agile Projects: A Machine Learning-Driven Empirical Model

Karthik Raja Anandan, et al. — International Journal of Information Technology (2021)