Loukik Naik

San Francisco, CA, United States0

Software Engineer | MSCS @ UC San Diego

I’m a software engineer who enjoys building systems that ship and scale. I’ve worked across backend, systems, and ML-adjacent infrastructure, building APIs, real-time services, and production pipelines. I like owning problems end-to-end and keeping systems simple and reliable. I’m especially interested in: - Backend & systems engineering - ML / AI-powered products - Distributed systems & infrastructure MS in CS from UC San Diego. Always learning, building, and happy to connect.

AI Fluency

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Projects

Verdict - Synthetic Market Research Agent

- Built a synthetic focus-group engine that runs 200–2,000 Claude personas against a product, returns a 1 - 5 purchase-intent PMF via structured output, clusters qualitative themes, and drops an Opus 4.7 executive brief - FastAPI, Sonnet 4.6, SQLModel, React + TypeScript end-to-end. - Designed a Temporal-shaped async workflow with ContextVar-based token attribution, so concurrent simulations in one process correctly bill each Claude call back to the right sim_id without threading IDs through every callsite. - Replaced an embedder-based SSR scorer (which clustered everything into a 3.0–3.6 band regardless of sentiment) with an LLM scoring path: Sonnet 4.6 reads each multi-turn interview, returns the full intent distribution, and grounds personas in live market data via the web_search tool. - Shipped reusable persona libraries, A/B variant comparison with side-by-side KPI deltas, per-call cost/latency telemetry (~$1 per 10-profile sim), and a Vite + React UI auto-deployed to verdict.loukik.dev — inspired by the PyMC × Colgate 2025 LLMs Reproduce Purchase Intent paper.

Podclipper - Long Podcasts to Reels in a Click

• Built a local pipeline that turns long-form podcasts into vertical 9:16 reels — Whisper, Claude, YOLOv8, and OpenCV chained end-to-end. • Designed a stage-based architecture with content-hash-keyed caching, so iterating on crop or prompt logic runs in seconds instead of re-transcribing. • Solved active-speaker tracking across hard shot cuts via per-shot x-center clustering with look-ahead crop seeding and mouth-motion → diarized-turn linking. • Shipped an LLM-as-judge quality gate, a React + Vite landing page, and GitHub Actions auto-deploy to podclipper.loukik.dev.

DraftIn - Keyboard-Driven LinkedIn Outreach Drafter

- Built a local-first Chrome MV3 + Node pipeline that drafts personalized LinkedIn outreach from a screenshot buffer - Alt+K stacks viewports across LinkedIn profiles and JD pages, Alt+L ships them through Oracle (browser-driven ChatGPT, no API key, no SaaS), and the result lands on the clipboard via pbcopy. - Designed it screenshot-as-source-of-truth - no DOM parsing, no LLM tokens in the browser — and used activeTab + captureVisibleTab so the same buffer works on any page (career sites, founder pages, anywhere the user scrolls). - Solved Chrome MV3's clipboard-after-focus-loss limitation by writing through the local server with pbcopy / xclip / clip instead of fighting the service-worker clipboard restriction from a toolbar gesture. - Tuned Oracle browser-mode flags (--browser-min-stable-ms 15s, 10-min ceiling, 4-min recheck) so mid-stream pauses during image analysis and company web-search lookups don't trip premature capture; shipped a React + Vite landing page with GitHub Actions auto-deploy to draftin.loukik.dev.

3D Vehicle Visualizer (Digital Twin + API)

• Built a browser-based 3D vehicle viewer with a FastAPI backend that controls vehicle state (speed, brake lights, doors) and syncs it with a React + Three.js frontend. • Designed a digital-twin architecture where the backend owns state + configuration, keeping the UI purely as a renderer. • Solved real-world GLB inconsistencies via semantic part mapping, custom hinge/axis overrides, and per-model configuration stored via API. • Implemented production-style UX patterns: optimistic updates with rollback, debounced writes, and polling for multi-client consistency.

Experience

Software Engineer

Eudia

Aug 2025 — Mar 2026 · Palo Alto, California, United States

• Owned the Mergers & Acquisitions backend service end-to-end, building and operating the core infrastructure for an agent-based AI system for large-scale legal document analysis in production. • Partnered closely with lawyers and product managers to design and ship product features, translating legal workflows and requirements into scalable platform capabilities. • Designed and shipped backend APIs serving as the control plane for AI agent execution, managing document ingestion, run orchestration, result persistence, and retrieval of structured and tabular outputs. • Re-architected agent orchestration by migrating from Airflow to Temporal, enabling reliable execution of long-running, stateful agents with retries, idempotency, and deterministic behavior. • Built backend capabilities for multiple AI agents, including flexible document analysis, configurable PII redaction, Contract Comparison, and tabular review with schema-based inference and cell-level operations, backed by structured logging, workflow tracing, telemetry, and Kubernetes-native monitoring. • Built workflows coordinating multiple services, queues, and workers, addressing production challenges including duplicate execution, inconsistent state across retries, and downstream dependency failures. • Designed and managed Postgres database schemas and migrations using Alembic, delivering backward-compatible schema changes to support new agent capabilities. • Converted the service to a multi-tenant architecture, enforcing tenant-aware routing, strict isolation, and safe rollouts across live customers. • Managed the rollout of new backend features across staging, internal, and production environments using Kubernetes, Helm, and ArgoCD, supporting multiple customer deployments.

Contributor

OpenFilter

May 2025 — Aug 2025 · United States

OpenFilter is a universal abstraction for building and running computer vision workloads

Plainsight Technologies

Jun 2024 — Aug 2025 · 1 yr 2 mos

Machine Learning Engineer

Jan 2025 — Aug 2025 · San Francisco, California, United States

• Developed and deployed real-time image segmentation APIs using FastAPI for vision models including SAM and MobileSAM, enabling seamless integration into internal applications. • Containerized services with Docker and automated infrastructure deployment via Terraform and CI/CD pipelines, ensuring scalable, consistent rollouts. • Designed a model caching system using symlinks and config-driven scripts, reducing friction during builds and cutting cloud runtimes by avoiding redundant model downloads at runtime. • Created a Cron-triggered retraining pipeline that detects newly labeled data and launches Vertex AI training jobs, enabling continuous model updates. • Designed an OCR model evaluation framework utilizing edit distance, confidence scoring, and text similarity metrics to automate quality checks pre-deployment. • Designed and implemented a robust integration testing framework to validate end-to-end performance of the model generation pipelines for segmentation, object and keypoint detection tasks.

Machine Learning Intern - Computer Vision

Jun 2024 — Dec 2024 · San Diego, California, United States

• Implemented serverless functions on Google Cloud Functions for real-time video processing. • Developed and orchestrated Kubeflow pipelines on GKE for video preprocessing and filter evaluation, triggered by GCS data ingestion. • Created an environment calibration model for deriving environmental statistics from video streams. • Automated testing and deployment using GitHub Actions, PyPi, and Docker for production readiness. • Ensured reliability through end-to-end tests and continuous integration.

Graduate Research Assistant

UC San Diego

May 2024 — Jun 2024