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Vetted Data Structures and Algorithms Professionals

Pre-screened and vetted.

Data Structures and AlgorithmsPythonDockerGitJavaScriptReact
JF

Joel Franklin Stalin Vijayakumar

Mid-level AI/ML Software Engineer specializing in Generative AI and NLP

Remote5y exp
EmerjenceBoston University
Generative AIDeep LearningMachine LearningComputer VisionArtificial IntelligenceData Analysis+103
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DZ

Dylan Zhu

Screened

Mid-level Machine Learning Engineer specializing in computer vision and generative AI

Hoboken, NJ7y exp
Stevens Institute of TechnologyPurdue University

“Built and deployed an LLM/RAG system that uses differential privacy and distributional similarity checks to transform private data into a non-sensitive knowledge base while preserving utility. Also has experience demonstrating adversarial ML concepts (FGSM) to non-technical audiences by focusing on observable model behavior rather than implementation details.”

PythonNumPySciPyPyTorchScikit-learnTensorFlow+89
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AD

Ashank Dsouza

Screened

Mid-level Full-Stack Developer specializing in Node.js/React and cloud DevOps

Bengaluru, India4y exp
TecnotreeArizona State University

“Software engineer with startup and capstone experience who improved an ~8-hour database refresh workflow by moving API calls to asynchronous execution and then addressing API rate limits via throttling. Emphasizes performance profiling/logging, strong developer onboarding documentation practices, and disciplined Agile/Jira bug triage and expectation-setting with stakeholders.”

.NETA/B TestingAgileAngularAPI DevelopmentCI/CD+60
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JB

Jack Bacon

Screened

Intern Embedded/Robotics Engineer specializing in solar energy systems and autonomous navigation

Marriottsville, MD0y exp
TMEICVirginia Tech

“Robotics-focused engineer from a senior capstone who built the backend motion-control software for a semi-autonomous line-following vehicle split across two ESP32s. Experienced in ROS 2 (DDS, lifecycle nodes, QoS) and in bridging microcontroller telemetry to a laptop ROS 2 stack over UART with custom structured protocols, using Gazebo simulation to tune PID and validate behavior before deploying to hardware.”

Automated TestingCC++Code ReviewComputer VisionData Structures & Algorithms+90
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SS

Sarthak Singh

Screened

Mid-level Full-Stack Engineer specializing in cloud-native systems and LLM applications

Remote, USA4y exp
InfluencedUniversity of Maryland, College Park

“Customer-support/engineering background spanning Informatica PowerCenter ETL and IBM demos/workshops, with hands-on experience hardening data workflows for production (error tables/reject links, validation, restart strategies, alerting, performance tuning). Also demonstrates a clear, systems-level approach to diagnosing LLM/agentic workflow issues (prompt/RAG/tooling/memory) using instrumentation and iterative fixes, and has partnered with sales on POCs by defining success metrics and mapping solutions to customer architectures.”

Next.jsTypeScriptTailwind CSSAmazon DynamoDBLarge Language Models (LLMs)Python+104
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AA

Aditya Agrawal

Screened

Intern Software Engineer specializing in backend systems and data engineering

1y exp
Pocket FMBITS Pilani, Hyderabad

“Backend/AI engineer who has built and shipped two products: Know Founder (Python/SQL/AWS) scaling to 2,000+ users in the first month, and Unifr (unifr.online), an AI search visibility engine that queries multiple LLMs and turns responses into structured brand insights. Strong in production reliability/performance (Redis caching, indexing, precomputation) and in designing agentic workflows with guardrails, validation, retries, and human escalation.”

CC++PythonJavaSQLData Structures & Algorithms+74
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RK

Rohith kollu

Screened

Senior Software Engineer specializing in backend microservices, cloud, and full-stack systems

Dallas, TX7y exp
CiscoIndiana Wesleyan University

“Backend/platform engineer who has built and scaled production Java/Spring Boot + Kafka services on AWS/Kubernetes (1M+ msgs/day) and led reliability/performance fixes that restored SLAs (25–30% latency improvement; 99.9% uptime). Also shipped an AI customer-support chatbot end-to-end using retrieval + guardrails and rigorous evaluation/observability, improving resolution time 40% and satisfaction 25%, with a strong plan/execute/verify approach to agentic workflow reliability.”

Amazon CloudFrontAmazon CloudWatchAmazon EC2Amazon RDSAmazon S3Apache Hadoop+154
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DR

Dipanwita Rano

Screened

Entry-Level Software Engineer specializing in full-stack development and machine learning

College Station, TX0y exp
NatWestTexas A&M University

“Master’s CS candidate with backend internship experience modernizing live operational workflows at NatWest/NetWess, focusing on reliability improvements, safer CI/CD deployments, and incremental refactors using feature flags and rollback paths. Built FastAPI-based APIs with strong security patterns (JWT + 2FA/TOTP, centralized authorization, RLS) and demonstrated attention to edge cases like idempotency and data consistency in a Netflix-clone project.”

AgileArtificial IntelligenceCC++CI/CDCUDA+99
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ED

ESHWANTH D. G

Screened

Mid-level Robotics Software Engineer specializing in autonomous perception and sensor fusion

CA, USA4y exp
HoneywellUniversity at Buffalo

“Robotics engineer with Honeywell and Tata Motors experience deploying ROS/ROS2 autonomous mobile robot fleets into live factory environments, integrating sensors, safety PLCs, and on-prem services. Known for solving end-to-end latency and stability issues (including network spikes under load) using gRPC, Docker, and improved diagnostics—cutting diagnosis time from hours to minutes and achieving sub-150 ms control response.”

PythonC++CSQLBashGit+118
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SH

Sai Harshith Tanguturi

Screened

Mid-Level Software Engineer specializing in Java microservices and AWS cloud-native systems

Grapevine, TX3y exp
PaycomUniversity of Texas at Austin

“Full-stack engineer who has owned customer-critical analytics and course intelligence platforms end-to-end (React/TypeScript + Node/Express + SQL), including an internal self-serve Reporting & Analytics Center adopted by 1,000+ users. Demonstrates strong systems thinking across performance (2× faster heavy reports), reliability (feature flags, testing), and distributed architecture (RabbitMQ microservices with idempotency, DLQs, and correlation-ID observability).”

JavaPythonJavaScriptTypeScriptCC+++105
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SV

Sai Vamsi

Screened

Mid-Level Software Engineer specializing in backend microservices and cloud-native systems

TX, USA4y exp
ServiceNowUniversity of Arkansas at Little Rock

“ServiceNow engineer who built an AI-powered ticket summarizer end-to-end (RAG with vector DB + GPT, Redis latency optimizations, fallback summarization, and a React UI widget for agent feedback). Also has hands-on ROS 2 experience building real-time sensor-fusion nodes (LiDAR/IMU), debugging SLAM/navigation issues via rosbag + EKF tuning, and bridging heterogeneous robots by translating ROS 2 topics to MQTT/JSON. Strong DevOps background with Docker, Jenkins CI/CD, and Kubernetes orchestration for scalable deployments.”

JavaPythonJavaScriptReactAngularRedux+128
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YS

Yamini Sunkari

Screened

Mid-level Software Development Engineer specializing in C++ and EDA toolchains

Frisco, TX3y exp
The University of Texas at DallasUniversity of Texas at Dallas

“Worked at AMD on Vivado tool releases, focusing on adding and integrating new IP/SoC functionality into the Vivado flow and validating expected behavior through testing. Comfortable engaging with customers and open to travel for hands-on customer-facing work.”

CC++JavaPythonMySQLSQL+52
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PA

Prachika Agarwal

Screened

Senior Solutions Architect and Data Analyst specializing in cloud data platforms and experimentation

New York, NY4y exp
Ovative GroupNYU

“Software engineer who built and scaled an internal automation/auditing tool for analyzing Google and Adobe tagging containers, adopted by 13 internal clients and saving ~15 hours per audit. Has experience shipping containerized, Kubernetes-orchestrated systems and integrating OpenAI APIs into an agentic chatbot feature (plus prior NLP chatbot work during a Cyber Peace Foundation internship).”

A/B TestingAgileCSSCC++Data Analytics+69
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FB

Fenil Bhimani

Screened

Mid-level Full-Stack Developer specializing in FinTech and Healthcare systems

3y exp
CitigroupCal State Fullerton

“Open-source contributor who improved React Query’s caching/subscription behavior to reduce unnecessary re-renders via debouncing and batched updates, validated with benchmarking and extensive tests. Also maintained a Flask extension and resolved production background-task hangs by tracing Redis connection handling issues, adding cleanup/retry logic and troubleshooting docs. In a fast-paced startup, owned the design of a Celery+Redis multi-queue background processing system with Prometheus-based observability.”

JavaJavaScriptPythonSQLC++React+106
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MS

Mukul Sai Pendem

Screened

Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps

United States (Remote)4y exp
Saayam for AllNortheastern University

“Backend engineer with strong Python/FastAPI microservices ownership, including an ML-serving service with embeddings, async DB access, and Redis caching to reduce latency under high load. Experienced deploying and operating containerized services on Kubernetes using GitOps (Argo CD/Helm) with automated CI/CD, plus hands-on Kafka streaming pipeline tuning and enterprise migration work (Infosys) using blue-green/active-passive strategies.”

AgileAnsibleAPI GatewayApache CassandraAuthenticationAWS+147
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NE

Nour Elaifia

Screened

Junior Full-Stack/AI Engineer specializing in enterprise AI agents and web platforms

San Francisco, CA3y exp
Bland AIMinerva University

“Forward Deployed Engineer focused on taking enterprise LLM voice agents from prototype to production. Led a turnaround on a high churn-risk account by building a custom nested-API integration and preprocessing layer that enabled the LLM to reason over complex order hierarchies, cutting call handle time from 15 minutes to 2 minutes and driving expansions. Strong in real-time agent/workflow debugging, developer workshops, and sales partnership for adoption.”

PythonJavaScriptTypeScriptNode.jsReactNext.js+69
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RK

Ramtin Kazemi

Screened

Junior Full-Stack Software Engineer specializing in Django, AWS, and AI/ML

San Diego, California1y exp
FOMOUniversity of San Diego

“Full-stack engineer who built and owned an AI-powered personal statement editor in Next.js (App Router + TypeScript), including dynamic routing, server-side data fetching, and typed API route handlers. Post-launch, they handled production monitoring/debugging and shipped reliability/performance upgrades (rate limiting, retries, rollback, DB indexing), and report a 40% latency reduction using Suspense/streaming and React concurrency patterns. Also implemented a durable Temporal-orchestrated AI document workflow with robust retry/idempotency strategies.”

Audit LoggingAWSCI/CDClaudeC++Data Structures and Algorithms+111
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OM

Owen Marcione

Screened

Intern Software Engineer specializing in embedded systems and full-stack AWS/React apps

1y exp
California Cybersecurity InstituteCal Poly San Luis Obispo

“Robotics software developer building an ESP32/FreeRTOS wheel-encoder driver for a differential-drive robot with PID velocity control and ROS2 odometry publishing. Has implemented vision-based human tracking (DepthAI) and an obstacle map + EKF sensor fusion using IMU and LiDAR, with a simulation-first debugging workflow (Gazebo, Foxglove) and Dockerized environments; plans to extend to Nav2 + SLAM Toolbox for building-scale mapping.”

CC++PythonJavaJavaScriptSQL+80
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NR

Naga Renuka Kandi

Screened

Junior Software Engineer specializing in cloud, full-stack development, and Generative AI

Remote, USA2y exp
Handshake AI LabNortheastern University

“Built and shipped a production Chrome extension (Promptly) that lets users select text on any webpage and transform it in place (rewrite/shorten/translate) using on-device AI plus external LLMs. Implemented a custom lightweight orchestration layer for prompt chaining, context flow, and output validation, and tackled tricky browser Selection API issues to preserve formatting while keeping the UX simple and fast.”

PythonJavaJavaScriptTypeScriptFastAPINode.js+87
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AT

Avantik Tiwari

Screened

Junior Data Scientist / Big Data Engineer specializing in ML, LLMs, and analytics platforms

Tempe, Arizona3y exp
Arizona State UniversityArizona State University

“Backend/data platform engineer who led a major redesign of a hybrid streaming+batch analytics platform processing 10+ TB/day (Airflow/Hive/BigQuery) with strong data-quality automation. Also built a production RAG PDF assistant with concrete mitigations for hallucinations and prompt injection (re-ranking, grounding, verifier step) and has deep experience executing low-risk migrations (dual-write, blue-green, rapid rollback) and implementing JWT-based row-level security.”

PythonSQLJavaJavaScriptMySQLPostgreSQL+112
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CW

Connor White

Screened

Junior Machine Learning Engineer specializing in GPU-accelerated computer vision

College Station, TX5y exp
Los Alamos National LaboratoryTexas A&M University

“Robotics software lead from Texas A&M Aggie Robotics who built WoopLib, a SLAM-based vision/navigation library using PID pure pursuit. Has hands-on ROS/ROS2 and Jetson Nano experience integrating Intel RealSense (T265/D435i) with wheel odometry for accurate state estimation, including compiling deprecated sensor support from source and optimizing by moving to Python with C++ bindings and serial streaming to a microcontroller.”

Machine LearningDeep LearningComputer VisionObject DetectionPyTorchCUDA+86
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YS

Yuvraj Singh Chauhan

Screened

Entry-level AI/ML Engineer specializing in LLMs, RAG, and DevOps automation

Bangalore, India1y exp
RapidFortThapar Institute of Engineering and Technology

“Built and owned a production-scale AI-driven software release/version intelligence platform orchestrated via GitHub Actions that tracks 1000+ upstream repositories and automatically generates SLA-bound JIRA upgrade tickets for hardened container images. Replaced brittle regex/PEP440 parsing with an LLM-based semantic filtering layer plus deterministic validation to handle noisy/inconsistent GitHub tags at scale, with monitoring for coverage, latency, and correctness validated against upstream ground truth.”

API IntegrationBashComputer VisionCC++Data Analytics+71
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