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Vetted C++ Professionals
Pre-screened and vetted.
Jianbo Wu
Mid-level AI/ML Engineer specializing in LLM reasoning and inference optimization
“Former Field Application Engineer at TestTorrent supporting proprietary hardware deployments. Built and integrated customer-requested benchmarking (including MLPerf-style work) by adapting GPU benchmark implementations and validating performance against NVIDIA baselines, plus delivered a backend fix that enabled customer performance testing and helped close a deal. Also has experience running models on AWS/GCP with multi-instance cost optimization techniques like memory offloading.”
Kanan Bandaliyev
Junior Software Engineer specializing in AI, computer vision, and medical imaging
“Unity developer with deep GPU compute experience who shipped a web-deployed CAD-style app requiring real-time mesh manipulation, solving performance and browser memory-limit issues via compute shaders and mesh chunking. Built an independent Unity gravity simulation using Schwarzschild approximation and geodesic integration, and has also worked on game-engine threading/job-queue architecture using AI-assisted workflows.”
Aniket Janrao
Junior Data Scientist specializing in healthcare ML and clinical NLP/LLMs
“Healthcare-focused LLM engineer who has built two production clinical applications: an automated structured clinical report generator from physician-patient conversations and a RAG-based chatbot for retrieving patient history (procedures, allergies, etc.). Demonstrates strong applied RAG expertise (overlapping chunking, entity dependency graphs, temporal filtering, graph RAG) to reduce hallucinations/omissions and partners closely with clinicians to automate hospital workflows.”
Yijun Chen
Senior Full-Stack Software Developer specializing in IoT and cloud systems
“Frontend-focused engineer who built a full movie recommendation system from concept to production, comparing classic collaborative filtering with LLM-based recommendation approaches on AWS. Emphasizes scalable architecture, strict TypeScript data contracts, and high-quality Next.js/React UI patterns (defensive states, scoped state management, performance optimization) with disciplined QA and feature-flagged rollouts.”
Ramtin Kazemi
Junior Full-Stack Software Engineer specializing in Django, AWS, and AI/ML
“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.”
Mukundan Sridharan
Executive Technology Leader (CTO) specializing in IoT sensing, AI/ML, and RF/embedded systems
“Currently a startup CTO who thrives on building new technology stacks and rapidly turning technical ideas into products. Interested in partnering with a CEO/business team to commercialize embedded/edge concepts such as multi-sensor drone localization (video/audio/RF with SDR), low-cost solar+battery power nodes networked via LoRa, and an Amazon Sidewalk/LoRa connectivity device with cloud management.”
“Generalist troubleshooter with experience debugging across C (memory leaks with Valgrind), Python (bug tracing to meet deadlines), and VHDL (hardware-related issues), plus some exposure to production deployments and networking issue resolution. Has supported customers remotely and emphasizes calm, patient communication during incident resolution.”
Jake Lee
Junior Full-Stack/Systems Engineer specializing in AI, embedded systems, and healthcare apps
“Led architecture for “Solstice/Solstis,” a safety-aware, hands-free AI medical assistant that guides users through minor emergencies with a structured, state-machine-driven LLM agent integrated with device hardware. Built RAG grounded in Red Cross procedures plus guardrails, fallbacks, and emergency escalation, and improved real-world usability by shifting from open-ended chat to a deterministic step-by-step workflow measured via completion rate, repeat prompts, and latency.”
Soham Patil
Junior Cloud & AI/ML Engineer specializing in AWS GovCloud and MLOps
“Robotics software engineer with hands-on ROS 2 autonomy experience on an obstacle-avoiding quadrotor (ROS 2 + Gazebo + PX4 + Nav2/SLAM), including custom work to extend Nav2 into a 3D aerial domain and output PX4 trajectory setpoints. Also built cost-saving ML infrastructure (PostgreSQL + AWS data-cleaning pipeline) and improved object detection accuracy by 40% using CUDA/PyTorch, with strong containerization and CI/CD practices (Docker + Kubernetes, aggressive version pinning) to prevent environment drift.”
Chandra Shekar Akkandra
Mid-level AI/ML Engineer specializing in fraud detection and risk analytics in Financial Services
“Finance-domain ML/LLM engineer who has shipped production systems including a RAG-based financial insights assistant with a custom post-generation validation layer that verifies atomic claims against retrieved source text to prevent hallucinations in compliance-critical workflows. Also built large-scale MLOps automation on AWS using Kubeflow + MLflow + CI/CD for fraud detection and credit risk models processing 500M+ transactions/day with a 99.99% uptime goal, and partnered closely with JP Morgan risk/compliance stakeholders on NLP-driven compliance monitoring.”
Prateek Sahay
Senior Robotics Software Engineer specializing in autonomous navigation and robotic manipulation
“Robotics software engineer with deep ROS/ROS 2 autonomy experience across warehouse fleets (Knapp delivery robots and quadrupeds), spanning SLAM, EKF-based sensor fusion localization, Nav2, and behavior-tree mission orchestration. Built a simulation-first testing approach using Isaac Sim Replicator with Dockerized, statistically analyzed repeat runs to catch nondeterminism, and personally owned real-world validation. Also developed a custom UR10 singularity-check ROS node based on manipulability.”
Meghanath kethireddy
Mid-level Full-Stack/Backend Engineer specializing in Java microservices and cloud platforms
“PayPal ML/AI practitioner who built and productionized a hybrid recommendation engine (BERT/LLM embeddings + collaborative filtering + XGBoost ranking) on AWS with end-to-end MLOps and orchestration. Addressed real-world issues like cold start and embedding latency (ONNX, clustering, caching, PySpark/Delta Lake) and drove a 27% lift in upsell conversion via A/B testing and stakeholder collaboration with marketing.”
Mukul Sai Pendem
Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps
“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.”
Joseph Winston
Executive Systems Architect specializing in distributed edge-to-cloud and real-time data platforms
“Has worked across multiple startup stages from pre-funding through Series D and emphasizes rigorous idea validation through direct conversations with both end users and purchasing decision-makers. Interested in applying NLP to automate summarization/abstracting of highly technical articles, with a balanced view of entrepreneurship that prioritizes health and family.”
Ram Jayesh Parekh
Junior Data Analyst specializing in ML, NLP, and cloud data pipelines
“Built and deployed a GenAI-powered PhD career intelligence platform at NYU that maps academic backgrounds to career paths and converts long academic CVs into job-ready resumes. Stands out for treating LLM systems as structured production pipelines—combining NLP extraction, embeddings, orchestration, and AWS deployment—to improve recommendation quality and cut resume preparation time by 70%.”
Kirtana Krishnan
Junior Software Engineer specializing in AI-powered full-stack applications
“Full-stack product engineer with hands-on ownership of both a real-time community Q&A platform and a production payroll reorder batching system. Stands out for combining backend architecture, React frontend work, and pragmatic performance improvements, including a 2-3x speed gain through batching and thoughtful UI/UX refinements that reduced user errors.”
Rohit Vibhu Channananjundarya
Mid-level Software Engineer specializing in distributed systems and full-stack platforms
“Engineer who treats AI as a force multiplier rather than a replacement for judgment, with hands-on experience using tools like Claude Code, Cursor, Copilot, and Codex across planning, coding, testing, and review. Particularly notable for building a multi-agent PR review system that automated summarization, risk scanning, schema validation, and test suggestions, helping the team shift reviewer time toward architecture and business logic.”
Kevin Pham
Junior Software Engineer specializing in full-stack and iOS development
“Built and shipped a production Python service integrating with a helium mass spectrometer for real-time sensing and remote control/monitoring. Combines hardware integration, observability, and Playwright-based automation expertise, with a strong track record of turning brittle or ambiguous real-world processes into reliable systems— including reducing dashboard automation failures from about 20% to under 2%.”
Sai V
Mid-level Software Engineer specializing in backend systems and FinTech
“Built an internal RAG assistant for financial documents using FastAPI, OpenAI APIs, and vector search, improving document search speed and reducing manual effort for the business team. Stands out for a pragmatic approach to AI engineering: uses AI heavily for productivity, but keeps human judgment central and has designed retrieval, validation, and summarization workflows end-to-end.”
Nakhle Kazwah
Principal Software Architect specializing in object-oriented enterprise systems
“Candidate explicitly stated they do not have production agentic/LLM or generative AI experience, aside from spending a few hours becoming familiar with the process. Compensation expectation stated as 225,000.”
Rodney Daniel
Junior Software Engineer specializing in full-stack, AI/ML, and systems development
“Full-stack product engineer with hands-on experience building a React/serverless/SQL e-commerce platform for Haagen-Dazs and improving consumer UX in a location-based animal discovery app. Stands out for pairing strong technical fundamentals—component architecture, SQL performance tuning, reusable primitives—with measurable product outcomes like 40% more completed orders, 25% customer growth, 95% navigation accuracy, and 20% fewer device malfunctions.”
Yash Priyadarshi
Junior Software Engineer specializing in distributed systems and cloud infrastructure
“Backend/distributed-systems engineer who built a Golang distributed key-value store on AWS using Multi-Paxos, WAL, and non-blocking gRPC replication (cutting write latency ~40%) and proactively addressed tricky failure modes like leader-election livelock. Also developed a Python/Kubernetes cost-optimization scaling engine deployed with Helm/Terraform, delivering ~$40K annual savings while sustaining 99.99% uptime, and drives contract-first API development (OpenAPI/Swagger) to speed frontend integration.”
Sai Sri Kolanu
Mid-level AI Engineer specializing in LLMs, RAG, and production ML systems
“Built and shipped an AI-powered RAG diagnostic assistant at Ford for EV technicians, integrating GPT-based models with LangChain, FAISS, and SageMaker into real technician workflows. Stands out for combining strong production LLM architecture with practical safety guardrails, monitoring, and measurable impact: 45% better diagnostic accuracy and roughly 30 minutes saved per case.”
VIJAYSHREE VAIBHAV
Intern software engineer specializing in backend and AI automation
“Early-career software/AI intern with startup and hackathon experience who blends backend engineering with product communication and user-feedback-driven iteration. Worked in a fast-paced SaaS environment at Airmeet and has experience pitching technical products, refining onboarding/workflows, and thinking beyond pure implementation toward adoption and growth.”