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Vetted C Professionals
Pre-screened and vetted.
Ashritha G
Mid-Level Software Development Engineer specializing in distributed systems and cloud microservices
“Software engineer with enterprise, customer-facing delivery experience across Outlier AI and Wipro—builds and productionizes workflow and integration solutions with a strong focus on real-world performance and reliability. Delivered a Firestore/Redis-backed real-time pipeline that cut page load times by 20% and held consistent performance across 10,000+ sessions, and has hands-on production incident experience stabilizing high-traffic microservices via caching, indexing, and safe canary deployments.”
Raunak Bandyopadhyay
Intern-level Full-Stack Engineer specializing in AI and web systems
“Backend-focused intern in telehealth who combined engineering, QA leadership, and emergency infrastructure ownership. Built a text chat feature and an OpenAI-powered therapy chatbot, then stepped up to rebuild AWS infrastructure after it was accidentally deleted, while also improving chat responsiveness and reporting a 30% engagement lift.”
Oleg Strakh
Executive robotics architect specializing in embedded AI and autonomous systems
“Founder of Workaholic-Robotics, a self-funded physical AI agriculture robotics startup, with hands-on experience spanning product development, customer discovery, commercialization, and fundraising prep. Brings a pragmatic, capital-efficient approach shaped by direct work with growers, dealers, and OEMs, plus accelerator experience through Innovate EU and Grishin Robotics Accelerator in London.”
Kunal Doshi
Senior Full-Stack Software Engineer specializing in cloud-native platforms and AI/NLP
“Full-stack engineer at an early-stage startup (AirKitchenz) who owned the hourly booking/availability and first paid booking flow end-to-end—React/TypeScript frontend, Node backend, Postgres modeling, and Stripe payments/webhooks. Experienced operating production on AWS (EC2/Elastic Beanstalk, Docker, RDS, CloudWatch) and building reliable, idempotent integrations while iterating quickly in a pre-PMF environment through direct host/renter feedback.”
DHYAN PATEL
Mid-level AI Engineer specializing in NLP and production ML systems
“AI/LLM engineer who has shipped production RAG chatbots using LangChain/OpenAI with FAISS and FastAPI, focusing on real-world constraints like context windows, concurrency, and latency (reported ~40% latency reduction and <2s average response). Experienced orchestrating AI pipelines with Celery and fault-tolerant long-running workflows with Temporal, and has applied NLP model tradeoff testing (Word2Vec vs BERT) to drive measurable accuracy gains.”
VenkataJyothiPriya Mulaka
Entry-Level Data Scientist specializing in ML, Azure, and LLM applications
“ML/computer-vision practitioner who shipped a CycleGAN-based bilingual handwriting translation demo (English↔Telugu) for low-resource scripts using unpaired datasets, focusing on preserving handwriting style and real-time deployment via Gradio. Also delivered a medical imaging pipeline by fine-tuning ResNet-50 and ViT-B/16 for pneumonia detection, emphasizing reproducibility, measurable evaluation, and stakeholder-friendly iteration.”
Varun Reddygari
Junior Software Engineer specializing in backend, cloud, and LLM-powered search
“Python backend engineer (BetterWorld Technology) who owns microservice systems end-to-end on Azure, including Kubernetes deployments, CI/CD, and production monitoring/alerting. Has hands-on experience integrating SQL/NoSQL (including Cosmos DB with vector search/graph workflow) and has built a Kafka + Spark Streaming pipeline to Snowflake with a reported 40% latency reduction.”
Aditya Mustyala
Mid-level Full-Stack Developer specializing in healthcare and scalable web platforms
“Software engineer experienced delivering customer-facing, real-time industrial monitoring dashboards (motors/shafts/turbines) by partnering directly with end users to refine charts, alerts, and performance. Strong in API/platform integrations and production troubleshooting—uses feature flags, logging, validation/mapping, containerization, and performance testing to keep systems stable while iterating quickly.”
Ziqi Xia
Intern Full-Stack Software Engineer specializing in web apps and AI integrations
“Computer science-oriented builder developing an iOS receipt-splitting app for real users (roommates), focusing on login security, receipt history storage, and future web access for broader usability. Demonstrates a practical, customer-facing mindset with structured integration/debugging practices (Dockerized environments, incremental testing, rollback strategy) and prior experience in communication-heavy retail/bakery roles.”
Kunal Patil
Senior Game Developer specializing in Unreal/Unity gameplay and graphics systems
“Unreal Engine gameplay programmer with shipped experience on Five Nights at Freddy’s (including Ruin), spanning end-to-end systems like save/load + checkpoints, math-heavy spline-based AI movement, and player movement tuning. Also implemented a networked PvP dash using Unreal’s prediction pipeline (FSavedMove_Character) with server-authoritative validation, and has demonstrated strong debugging under stress-test conditions.”
Ravi Gupta
Mid-level Software Engineer specializing in Generative AI automation and secure platforms
“Backend/security-focused engineer from VeroTX who built an IdP service (Spring Boot + MongoDB on GCP) for an AI workflow platform and drove major latency improvements via caching and query/index optimization. Also shipped an AI loan-processing agent using LangChain/LangGraph, owning the document ingestion + vector database layer and designing a reliable multi-step workflow with retries, monitoring, and human-in-the-loop safeguards.”
“Game design capstone project owner who built and tuned a full steal/sell/upgrade progression economy for a house-robbery game, including item weight/value balancing, upgrade pacing, and difficulty gates (police/NPC detection). Iterated via playtests and basic telemetry signals (purchase rates, item selection) and implemented a code-driven item attribute system to speed tuning, while also negotiating scope tradeoffs with the team around adding minigames.”
Harsh Chauhan
Junior AI Engineer specializing in Generative AI, RAG, and NLP
“AI/LLM engineer who has shipped a production RAG platform at Ticker Inc. on GCP (Qdrant + Postgres) delivering sub-second retrieval over 550k+ items, with measurable gains in latency and answer quality (HNSW optimization, MMR re-ranking). Also built an asynchronous LangChain/LangGraph multi-agent research system (10x faster cycles) and partnered with Indiana University doctors on synthetic patient records and ML error analysis using clinician-friendly F1/loss dashboards.”
Moore Macauley
Intern Backend Developer specializing in AI, multi-agent systems, and computer vision
“Backend-focused Python engineer who built core systems for an AI beauty-advice product: converting facial-recognition landmarks into usable facial measurements and dynamically shaping chatbot context for personalized guidance. Also worked on high-volume data ingestion at AINVESTgroup, improving agent context selection via a RAG database when upstream tags were unreliable, and has strong Git/GitOps + automated testing practices from rapid-deadline delivery environments.”
Ronit Shetty
Entry-level Robotics Engineer specializing in SLAM, sensor fusion, and embedded avionics
“Robotics software engineer focused on perception/SLAM and systems integration, recently built a quasi-dynamic mapping pipeline to track and reconstruct articulated objects (e.g., drawers) from RGB video using SAM2, COLMAP SfM, and 3D Gaussian Splatting. Also has strong ROS2 sensor-pipeline experience (custom messages, MCAP rosbag deserialization, tf2) and demonstrated real-time performance tuning by accelerating an ICP-based LiDAR SLAM component ~30x (from ~3s to <100ms per frame).”
Sonam Chhatani
Mid-level AI Engineer specializing in causal inference and LLM research
“LLM engineer who has deployed a production system combining LLMs with causal inference (DoWhy) to enable counterfactual “what-if” analysis for experimental research, including a robust variable-mapping/validation layer to reduce hallucinations. Also partnered with non-technical operations leadership at Irriion Technologies to deliver an AI-assisted onboarding workflow that cut onboarding time by 50% and reduced manual errors by ~40%.”
Mohammed Mudassir Hussain Shaikh
Entry-Level Full-Stack Software Engineer specializing in serverless AWS and AI applications
“Built and deployed serverless AWS applications (Lambda/S3/RDS Proxy) including a NASA L’Space React + Python data analysis tool, focusing on performance for large datasets. Demonstrates strong cloud troubleshooting across compute and networking (CloudWatch-driven diagnosis, EC2 scaling, security group fixes) and a user-driven iteration loop that improved product usability with dynamic filtering and interactive UI.”
Sujay Surendranath Pookkattuparambil
Mid-level Machine Learning Engineer specializing in computer vision and reinforcement learning
“Early-stage engineer with hands-on embedded prototyping experience (Arduino/Raspberry Pi) who helped build an award-winning smart glasses project enabling phone notifications via Bluetooth. Strong computer vision performance optimization background, including accelerating 120 FPS inference by moving from TensorFlow to PyTorch and deploying through ONNX + TensorRT quantization, plus Docker-based GPU deployment and CI/ML practices.”
Adam Danicki
Entry-Level Software Engineer specializing in full-stack and machine learning
“Robotics software builder who delivered an end-to-end gesture-controlled drone system using an ESP32+IMU stream and real-time ML inference mapped to Tello SDK commands. Drove reliability improvements by instrumenting the pipeline with timestamps/logging and matching training vs runtime preprocessing, reaching ~94% gesture classification accuracy; experienced with Docker/Compose for reproducible multi-service deployments.”
Milan Sharma
Mid-level Software/Systems Engineer specializing in Python, Linux, and network testing
“Entrepreneurial product builder who has shipped two live App Store apps (Pixo content-based product marketing platform and Clutch AI dating reply helper). Also helped build a real-estate seller platform end-to-end, using AI matching to find buyers and contributing to onboarding nearly paying users and generating active MRR.”
Vishesh Kumar
Intern Software & AI Engineer specializing in distributed systems and LLM applications
“Stony Brook Fall 2024 capstone contributor who built a ROS2-based warehouse mobile robot prototype, owning perception and SLAM integration end-to-end. Strong in real-time robotics optimization on Jetson Orin (TensorRT/CUDA, ROS2 tracing/Nsight) and in distributed ROS2 communications (DDS discovery/QoS, MAVLink-to-ROS2 bridging), with a full simulation/testing/deployment toolchain (Gazebo, CI tests, Docker/K3s).”
Michelle Gurovith
Intern Software Engineer specializing in iOS (Swift/SwiftUI) and distributed systems
“Built a fault-tolerant distributed IoT sensor network on Raspberry Pi using a token-ring protocol, implementing leader election, timeout-based failure detection, and dynamic reconfiguration when nodes drop mid-round. Focused on reliability and data integrity, including exactly-once processing semantics backed by a MySQL backend and socket-level instrumentation to debug real-time coordination issues.”
Mayur Agrawal
Entry-Level Backend Engineer specializing in analytics automation and cloud data pipelines
“Forward Deployment Engineer focused on application security and production integrations, with hands-on experience hardening API-driven ticketing systems (JWT/RBAC/rate limiting/log redaction) and implementing CI/CD security controls (Bandit SAST, SCA, container hardening). Strong in diagnosing peak-load production issues using logs/metrics/infra signals and driving durable fixes like adaptive throttling and backoff, while aligning engineering, business, and leadership stakeholders on risk and SLA impact.”
Pooja Dhanaji Bodke
Junior Data Analyst specializing in BI, analytics, and machine learning
“Analytics professional with hands-on experience turning messy Excel-based operational data into SQL/Python pipelines and Power BI dashboards, including a production bottleneck project that improved workflow efficiency by 20%. Also brings applied machine learning experience from a Databricks/PySpark loan risk scoring project using logistic regression and XGBoost on large-scale S3 data.”