Vetted Linux Professionals

Pujan Parikh

Screened

Staff Front-End Engineer specializing in enterprise cloud and AI-driven applications

Redwood City, CA8y exp

“Frontend-leaning architect with deep React/TypeScript expertise who has repeatedly owned platform-level problems across Oracle Health, Oracle Cloud, and Veritas. Stands out for building cross-plugin routing standards for a next-gen EHR, high-scale real-time observability dashboards, and even stepping into backend/AI infrastructure design with Kafka- and RAG-based systems.”

“ML engineer with production experience at Goldman Sachs and Medtronic, focused on real-time AI systems in fraud detection and healthcare. Brings a rare mix of backend ML infrastructure, MLOps, and product-minded UX thinking, including dashboard and API design that made complex model outputs usable for analysts and clinical users.”

Anshika Bajpai

Screened

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps

Bloomington, IN4y exp

“Engineer with impactful experience at Palo Alto Networks and Optum, focused on production automation and AI-powered internal tools. Built and owned an end-to-end RAG knowledge system adopted by 1000+ internal users with roughly 75% faster response times, and also transformed a legacy Optum coverage-feed workflow from 500+ minutes to under 3 minutes through data standardization and microservices refactoring.”

“AIX/IBM Power Systems engineer with hands-on production incident leadership in a regulated banking environment, using deep OS-level tooling to diagnose CPU entitlement and memory pressure issues. Experienced with HMC/vHMC, VIOS, and zero-downtime DLPAR resizing, plus PowerHA/HACMP clustering and validated failover testing. Also drives migration readiness via Bash/Python automation (60% manual-effort reduction) and phased AIX cloud/hybrid cutovers.”

“Software engineer with hands-on embedded/robotics coursework experience (Arduino sensor integration and input handling built from scratch without external libraries) and strong DevOps/engineering productivity impact at work, including leading a CI/CD enhancement that runs only impacted tests to catch issues before PR approval.”

“Robotics-focused candidate with multiple university robotics projects (MTE 380, MTE 544) and ROS 2 (Humble/Galactic) experience spanning perception, navigation, and simulation. Built a vision-based line-following and retrieval robot using HSV filtering and homography, and debugged real-time PID overshoot issues via timestamping/rate-limiting. Comfortable with distributed ROS 2 architectures (Python perception + C++ control), DDS/QoS, Gazebo testing, and Dockerized deployment.”

“Robotics engineer with a 2024 internship building an end-to-end software stack for an autonomous humanoid robot that follows natural-language audio commands to make coffee and deliver snacks, including perception (OpenCV), mapping, and ROS Navigation. Also contributing to a robotics foundation model effort by building data preprocessing pipelines using GroundingDINO and SAM2, and has multi-robot coordination experience with algorithms designed to handle real-world communication drops.”

“Backend engineer with hands-on experience scaling a Python/Flask incident-logging platform processing thousands of daily logs. Strong in performance tuning (PostgreSQL/SQLAlchemy query optimization, partitioning, summary tables) and reliability patterns (Redis caching, Celery background workers, Docker + Jenkins CI/CD), with some multi-tenant data isolation experience via separate DBs/schemas.”

“Customer-facing technical professional experienced in productionizing complex systems (including LLM/agentic workflows) and high-volume cloud data pipelines. Built and hardened a near-real-time data extraction/caching solution that significantly reduced latency and became a reusable pattern for other enterprise use cases; also runs developer demos/workshops with hands-on test environments and has driven 30–50% latency improvements.”

“AI/ML engineer with production experience building LLM-powered document intelligence and customer support systems in healthcare/insurance, emphasizing high-accuracy RAG, long-document processing, and robust monitoring/fallback mechanisms. Also automates and scales ML lifecycle workflows using Apache Airflow and Kubeflow, and partners closely with non-technical operations stakeholders to drive adoption.”

“Software engineer with experience building a Vue.js/TypeScript internal component library (with Jest testing standards) and improving JS runtime performance via profiling, code splitting, and lazy loading. Also led documentation and community support for a Python ML utility library, diagnosing metric-calculation bugs for imbalanced datasets and driving large reductions in support inquiries through targeted docs, tests, and rapid hotfixes in a startup environment.”

“Internship experience building production-oriented AI systems, including a real-time voice scam/spoof detector (RawNet + AASIST) hardened for noisy audio via aggressive augmentation and Zoom-based noise simulation, evaluated with EER on clean and wild datasets. Also built an LLM-driven UI automation agent using Playwright for apps like Linear/Notion with modular tool design, unit tests, and replayable scripted scenarios, and has AWS Step Functions experience orchestrating Lambda/Cognito workflows.”

“Founder/builder of an EdTech startup (robograde.io) who personally conducted on-site classroom discovery with teachers and rapidly iterated the product based on real-world feedback. Implemented a Canvas LMS integration and refined it through weeks of in-person testing, and handled a live production grading failure by quickly debugging and deploying a fix, then adding fault-tolerant/backup API design.”

“AI engineer with robotics perception experience at Forterra, building and deploying moving-object/obstacle detection models into real-time robot pipelines. Addressed training crashes/latency via sub-batch training and optimizer tuning, and improved debugging using ROS/ROS2 tooling with 3D voxel visualization and color-coded validation.”

“Platform-focused engineer experienced in productionizing ML/LLM systems: containerized a local prototype, implemented CI/CD, deployed to Kubernetes with scaling controls, and added monitoring/logging. Comfortable diagnosing real-time issues in LLM/agent workflows using logs/metrics and incident stabilization tactics, and supports sales calls by clearly explaining production scalability to unblock customer decisions.”

“Infrastructure-leaning engineer who has built real-time ML systems end-to-end: a Jetson-deployed adaptive Whisper ASR service (Flask + WebSockets, React/TS UI) and a high-throughput Postgres schema for live transcription. Also delivered customer-facing AI billing/OCR improvements for a dental startup (Dentite), boosting OCR performance by 38%, and has experience instrumenting open-source ML deployment stacks to add infrastructure visibility.”

“Data engineer with experience delivering an end-to-end pipeline handling ~3.5TB in a star-schema setup (fact + dimensions) and producing business-facing tables in Hive/Spark. Identified and resolved UAT-reported duplicate issues caused by joins through root-cause analysis, and also built automation to run Spark SQL metrics on weekly/monthly/quarterly cadences and distribute results to users.”

“Windows/VMware infrastructure project lead with experience managing 3,000+ servers across large enterprise environments (mentions Pfizerco, American Express, and FedEx). Focused on performance troubleshooting and stability using monitoring tools, plus security hardening and dependency/latency evaluation during on-prem to AWS/Azure hybrid migrations.”

“Data engineer focused on fraud and banking analytics who has owned end-to-end batch + streaming pipelines at very large scale (hundreds of millions of records/day). Built robust data quality/observability layers (schema validation, anomaly detection, alerting) and delivered low-latency serving via AWS Lambda/API Gateway with DynamoDB + Redis, plus external data ingestion/scraping pipelines orchestrated in Airflow with anti-bot protections.”

Ajay Madhusudhan Thumala

Screened

Junior Software Engineer specializing in data engineering and LLM applications

Irvine, CA1y exp

“Computer science engineer and master’s graduate who independently built a mechatronics-heavy capstone prototype: a smartphone concept for deafblind users using micro-actuator arrays for braille reading. Also has platform engineering experience at Quantiphi, deploying webhooks to Kubernetes and implementing GitOps-based CI/CD using AWS CodeCommit/CodeBuild and ECR.”

Yunxi Zhu

Screened

Entry-level Robotics & Automation Engineer specializing in robot learning and manufacturing automation

Houston, TX1y exp

“Robotics software engineer focused on real-time teleoperation and high-quality robot-learning data pipelines, including synchronized multimodal sensing (RGB-D, tactile, joint states) for Diffusion Policy training on a bimanual ALOHA robot. Strong ROS practitioner who debugs real-time control issues with ROS tooling and builds simulation environments in Isaac Lab and PyBullet; also packages data-collection stacks with Docker.”

Jen-Hung Chang

Screened

Mid-level Software Engineer specializing in cloud infrastructure and distributed systems

Hsinchu, Taiwan4y exp

“Backend/platform engineer who built an AI RAG system on FastAPI/Postgres/AWS with 10+ microservices, vector search optimization (ANN + two-stage re-ranking), and GitOps-driven CI/CD that cut deploy time from hours to minutes. Also deployed Java identity services on Kubernetes at TSMC for 200K+ users using ArgoCD/Azure Pipelines, and built a reliable real-time IoT pipeline (MQTT/Node/MongoDB) with strong consistency controls.”