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Krishna Panjiyar

Graduating May 2027 San Jose, CA Open to relocation

Krishna Panjiyar

Software engineer building production backends and ML systems.

Open to 2027 new-grad Software Engineer and Machine Learning Engineer roles. Also a fit for backend, full-stack, ML and data, developer tooling, and infrastructure roles.

I'm finishing an M.S. in Software Engineering & Data Science at San José State University, with 2.5+ years of production experience behind it. I've owned ML ranking APIs and microservices, built Spark and Hadoop pipelines, and written the test framework my Esri team adopted as its standard.

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Illustration of the Golden Gate Bridge over the bay at dusk Bay Area
Krishna Panjiyar smiling, outdoors at dusk

Krishna Panjiyar

Software Engineer · San Jose, CA

Open to 2027 new-grad roles

Photo of Krishna Panjiyar over an illustration of the Golden Gate Bridge.

  • 3K req/s

    Production ML ranking APIs

    Served up to 3K requests/sec and cut p95 latency by 20% to under 45ms.

  • 17

    Regressions caught at Esri

    My pytest framework (22 tests, 9 endpoints) became the team's standard and cut a full run from 15 to about 3.5 minutes.

  • 87%

    Precision@10, two-stage recommender

    Retrieval plus re-ranking reached 0.82 NDCG@10 and 0.78 Recall@20.

Projects

Pick the track you're hiring for

Each project is tagged by the kind of role it speaks to. The five case studies walk through the problem, the architecture, the tradeoffs, and the results.

Showing 6 projects.

More projects

  • LiDAR Point-Cloud Processing & 3D Perception

    ML

    C++/PCL pipeline over KITTI scans: voxel-grid filtering, RANSAC road segmentation, and Euclidean clustering of obstacles, visualized in 3D.

    C++, PCL, CMake, KITTI

Experience

Where I've shipped

  1. Software Engineering Intern, Esri

    May 2026 to Aug 2026

    • Built a Python/pytest framework for the ArcGIS Enterprise Uploads APIs: 22 test functions across 9 endpoints, 33 parametrized cases, and 9 subtests on Unix/Linux and Windows. The team adopted it as its standard test pattern.
    • Designed single-file and multipart upload workflows for files up to 200MB and caught 17 regressions manual testing had missed.
    • Replaced legacy ReadyAPI suites with reusable fixtures, cutting a full run from 15 to about 3.5 minutes. Used AI coding agents for scaffolding, with validation harnesses that checked the generated code.
    Developer ToolingBackend
    Krishna Panjiyar, far right, on stage with five fellow Esri interns, each holding a certificate in front of the Esri Intern Hackathon bannerOpen the full-size photo (opens in a new tab)
    Third place

    Esri Intern Hackathon 2026: PulseMap

    Third place at Esri's Weekend of Innovation 2026, the Esri Intern Hackathon, with team Arcitects for PulseMap. I built core app features: AI explanations, the 2D and 3D map, filtering, and English and Spanish support.

    Read the PulseMap case study

  2. Software Engineer, Feature Stack IT Inc.

    Jan 2023 to Aug 2025

    • Owned production ML ranking APIs and Java/Python microservices with Kafka and SQL, serving up to 3K requests/sec and cutting p95 latency by 20% to under 45ms.
    • Built Spark and Hadoop batch pipelines over 2M+ daily Kafka events, producing training sets and offline feature stores for inference.
    • Raised throughput by 30% near 10K concurrent users, cut production defects by 35% with JUnit/Selenium tests, and maintained Jenkins CI/CD and Prometheus/Grafana monitoring.
    BackendMLInfrastructure

  3. Software Engineer Intern, Neuroleap Corp.

    Apr 2021 to Sep 2022

    One role with two sides: I built the product, and I ran the systems, deployments, and monitoring behind it.

    • Product: built and shipped a real-time SwiftUI/Firebase iOS app and backend for cognitive-research data collection, used by a few thousand people, and improved data integrity and sync by 30%.
    • Infrastructure: handled all of the systems administration and DevOps, including Docker/Jenkins CI/CD and deployments, plus backend and infrastructure monitoring. Cut deployment time in half and added dashboards that sped up root-cause analysis.
    • Implemented ML data-preprocessing workflows and worked directly with product, research, and engineering.
    Full-StackInfrastructureML

How I work with AI

Fast with AI tools, strict about what ships

I use AI coding tools every day, and I treat what they produce like a pull request from a fast new teammate: useful, and never merged without review.

What I use them for

  • GitHub Copilot
  • Cursor
  • Claude Code
  • Codex
  • Planning and talking through a design before I write it
  • Scaffolding and implementation
  • Debugging and iteration
  • Edge-case discovery when writing tests
  • Agent workflows built from prompts, subagents, custom tools, and MCP servers

How I verify what they produce

  1. 01Every generated change goes through code review, same as anything I write by hand.
  2. 02Automated tests back it up, run on every platform the code ships to.
  3. 03I check performance and security, not just whether it runs.
  4. 04At Esri, validation harnesses checked agent-generated test code for correctness, performance, and security before it reached review.

Skills

Tools I've used in production and projects

Languages
PythonJavaGoJavaScript/TypeScriptC/C++C#SQLSwift
Backend
REST APIsGraphQLFastAPIFlaskSpring BootNode.jsNestJSMicroservicesEvent-driven systemsKafka
ML and data
PyTorchTensorFlowScikit-learnHugging FaceOpenAI APIRecommender systemsSparkHadoopPandasNumPy
Databases
PostgreSQLMySQLMongoDBRedisElasticsearch
Cloud and infrastructure
AWS (EKS, Fargate)DockerKubernetesCI/CDJenkinsGitHub ActionsNginxUnix/Linux
Testing and observability
pytestJUnitSeleniumPrometheusGrafana
Frontend
ReactNext.jsTypeScriptVite
AI coding tools
GitHub CopilotCursorClaude CodeCodex

Education

San José State University

Tower Hall at San José State University on a sunny day, framed by palm trees
San José State University, where I earned my B.S. and am finishing my M.S.

  • M.S. Software Engineering & Data Science

    San José State University

    Expected May 2027

  • B.S. Software Engineering

    San José State University

    December 2022

Relevant coursework: Data Structures & Algorithms, Distributed Systems, Machine Learning, Deep Learning, Operating Systems.

Contact

Hiring for 2027? Let's talk.

Email is the fastest way to reach me. I'm in San Jose, CA, open to relocation, and graduating in May 2027.

Krishna.Panjiyar789@gmail.comLinkedIn (opens in a new tab)Resume (PDF)