---
title: "Rajneesh Chaudhary - Machine Learning Scholar in Bengaluru | Tal"
description: "Meet Rajneesh Chaudhary, Software Engineer | Backend Development | C++ | Java | Python | DSA | Leetcode Knight ( Rating 1995 ) | Spring Boot | AWS | Distributed Systems | REST APIs based in Bengaluru. AI stack includes anthropic apis, antigravity, and claude code. Explore public work links includin..."
image: "https://tal.club/meet/rajneesh-chaudhary/share-image"
---

# Rajneesh Chaudhary on Tal

## Headline

Software Engineer \| Backend Development \| C\+\+ \| Java \| Python \| DSA \| Leetcode Knight \( Rating 1995 \) \| Spring Boot \| AWS \| Distributed Systems \| REST APIs

## About

I’m a Software Engineer with hands\-on experience in backend development, cloud\-native systems, distributed applications, and machine learning\. I have contributed to 4\+ CNCF projects, including Kubernetes, OpenTelemetry, Jaeger, Cilium/Hubble, and Meshery, working on runtime troubleshooting, concurrency, telemetry processing, lifecycle management, service integration, and observability workflows\. My software engineering experience spans Java, Python, Go, C\+\+, JavaScript, TypeScript, Spring Boot, FastAPI, React, REST APIs, gRPC, Docker, Kubernetes, Redis, PostgreSQL, and AWS\. I enjoy working on systems involving asynchronous processing, distributed workloads, APIs, debugging, testing, and deployment\. I’ve also built AI/ML applications involving RAG, FAISS, BM25, Llama, PyTorch, TensorFlow, EfficientNet, Transformers, FastAPI, and MLflow, including production\-style retrieval systems and machine\-learning inference services\. Problem solving is a major part of my development journey\. I have solved 1,300\+ LeetCode problems, reached LeetCode Knight, and regularly work on algorithms, data structures, and competitive programming\. Some highlights: • 4\+ CNCF projects contributed to • 1,300\+ LeetCode problems solved • LeetCode Knight — 1995 rating • Amazon ML Summer School 2026 — selected among 3,000\+ participants from 134,000\+ applicants • AlgoUniversity Technological Fellowship — selected among approximately 200 from 20,000 applicants • Research publication on LSTM\-based stock market prediction I’m interested in Software Engineering, Backend Engineering, Java/Spring Boot, Python, Cloud\-Native Systems, Distributed Systems, and ML/AI Engineering opportunities\. 📩 rajneeshrehsaan48@gmail\.com

## Location

Bengaluru

## AI stack

anthropic apis

antigravity

claude code

claude

cursor

gemini

## Work experience

Machine Learning Scholar at Amazon, Jul 2026 \- Aug 2026 · 2 mos, Bengaluru, • Selected among 3,000 participants \(\~2% acceptance\) from over 134,000 in Amazon ML Summer School 2026, an intensive technical program delivered by Amazon Applied Scientists and Researchers\. • Completed advanced coursework spanning Machine Learning, Deep Learning, Representation Learning, Unsupervised Learning, Generative AI, Large Language Models \(LLMs\), Agentic AI, Reinforcement Learning, Causal Machine Learning, Diffusion Models, and Flow Matching\. • Explored production\-scale AI and ML systems, including Retrieval\-Augmented Generation \(RAG\), Vector Search, Embedding Systems, Agent Evaluation, Tool Orchestration, Model Evaluation, MLOps, Inference Optimization, Model Robustness, Distribution Shift, and scalable deployment of foundation models\. • Studied modern causal inference techniques, including Propensity Score Methods, Inverse Probability Weighting \(IPW\), Augmented IPW \(AIPW\), Double Machine Learning \(DML\), Causal Forests, Heterogeneous Treatment Effect Estimation \(HTE\), and representation learning for causal ML\. • Actively participated in technical discussions and Q&A sessions with Amazon Applied Scientists and Researchers on LLM systems, reasoning models, AI agents, causal inference, production ML architectures, evaluation methodologies, representation learning, diffusion models, and scalable foundation model deployment\.

Open Source Contributor at Cloud Native Computing Foundation \(CNCF\), Feb 2026 \- Jul 2026 · 6 mos, Remote, • Investigated 20\+ runtime scenarios involving goroutine hot loops, memory growth, shutdown failures, event\-processing errors, and telemetry inconsistencies through structured debugging and root\-cause analysis\. • Integrated Kubernetes client\-go watchers with lifecycle workflows, validating concurrency, graceful shutdown, failure recovery, and asynchronous event processing across distributed workloads\. • Contributed to OpenTelemetry Collector and OTTL, including lifecycle synchronization, Prometheus exporter memory\-leak fixes, CORS configuration, and AST\-based constant folding for deterministic expressions\. • Supported contributions across 4\+ CNCF projects, including Kubernetes, OpenTelemetry, Cilium/Hubble, Jaeger, and Meshery, through issue investigation, code validation, documentation, and cross\-project collaboration\. • Developed an incident\-analysis dashboard using Next\.js, TypeScript, and Go, combining runtime diagnostics, metrics, distributed traces, and network insights for cloud\-native troubleshooting\.

UnderGrad Reinforcement Learning Research under Dr\. Ankur Jaiswal \(DoIT\) — Autonomous UAV Systems at ABV\-Indian Institute of Information Technology and Management, Jan 2026 \- Jul 2026 · 7 mos, \( Research under Dr\. Ankur Jaiswal, Department of IT, ABV\-IIITM Gwalior \) Designing and simulating an obstacle\-aware UAV path planning system for resource\-constrained IoT networks using deep reinforcement learning — combining classical graph algorithms with modern RL for multi\-objective mission optimisation\. • Formulated a D3QN \(Dueling Double DQN\) agent for adaptive, obstacle\-aware trajectory optimisation — state space encodes UAV pose, residual battery, obstacle proximity, and rendezvous\-point visit vector; reward jointly optimises data\-priority collection, collision avoidance, and energy cost\. • Modelled an 800×600 m IoT deployment \(20 sensor nodes, 3 cuboid obstacles at 128–148 m height > UAV operating altitude\) as a simulation\-driven testbed for RL policy evaluation\. • Implemented greedy dominating\-set rendezvous selection achieving 65% node compression \(20 → 7 stops\) with 100% network coverage guaranteed\. • Built a visibility\-graph \+ Dijkstra pipeline for collision\-free baseline trajectory planning under 3D obstacle constraints; baseline path ≈2,566 m at \~9\.2% battery utilisation\. • Exploring PPO as a continuous\-action extension over the D3QN baseline for smoother, energy\-efficient flight trajectories\. • Evaluating on path efficiency, battery profile, coverage completeness, and scalability to dense IoT deployments\.

Open Source Contributor at GirlScript Summer of Code, Jun 2025 \- Jul 2025 · 2 mos, Bengaluru, Contributed to open\-source repositories as part of GirlScript Summer of Code 2025 — submitting pull requests, participating in code reviews, and working within real maintainer workflows on GitHub\.

Software Development Engineer at AlgoUniversity, May 2025 \- Aug 2025 · 4 mos, Remote, Built and deployed a cloud\-native Online Judge on Kubernetes serving 50\+ daily active users\. • Designed a Redis Streams\-based distributed evaluation pipeline decoupling submission intake from sandboxed workers — 5× throughput improvement over the sequential baseline\. • Engineered Docker sandboxing with cgroups \+ SECCOMP per submission for secure, isolated code execution\. • Implemented JWT \+ OAuth 2\.0 \+ RBAC auth layer and automated CI/CD enabling zero\-downtime releases on AWS\. Small team, real production traffic, full ownership from design to deployment\.

ATF Scholar'24 at AlgoUniversity, Nov 2024 \- Apr 2025 · 6 mos, Hybrid, One of 200 selected from 20,000 applicants for AlgoUniversity's Technological Fellowship — a 6\-month intensive focused on competitive programming, system design, and industry\-level project building\. Trained in advanced DSA/CP under mentors including a Codeforces Master \(HFT @ Alphagrep\) and an ACM\-ICPC World Finalist \(Quant @ Tower Research\)\. Built and shipped production\-deployed projects using MERN, Docker, and AWS\. Completed a Summer SDE Internship equivalent as part of the program\.

## Education

Bachelor of Technology \- BTech, Computer Science & Engineering, ABV\-Indian Institute of Information Technology and Management

Senior Secondary, PCM, St\. xavier's High School

## Public links

- github: https://github\.com/Rajneesh180
- leetcode: https://leetcode\.com/rajneesh190

[View the original profile](https://tal.club/meet/rajneesh-chaudhary)

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