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Vetted MATLAB Professionals
Pre-screened and vetted.
Senior Full-Stack Engineer specializing in cloud-native SaaS and AI/ML integration
Mid-level SDET specializing in embedded firmware validation and test automation
Mid-level AI/ML Engineer specializing in multimodal and LLM (RAG) systems
Intern Computer Vision/ML Engineer specializing in mapping, localization, and scalable inference
Senior Data Scientist specializing in AI/Deep Learning and applied machine learning
Mid-level AI/ML Engineer specializing in GenAI agents and production ML systems
Mid-level Data Scientist/ML Engineer specializing in LLMs, NLP, and recommender systems
Director of Enterprise Analytics specializing in AI/ML for healthcare and insurance
Senior strategy and corporate development leader specializing in cybersecurity
Senior Software Test Engineer specializing in QA automation and API/E2E testing
Staff Platform/ML Engineer specializing in agentic AI, RAG, and cloud infrastructure
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Entry-level investment analyst specializing in digital assets and commodities
Mid-level Software Engineer specializing in distributed systems and full-stack development
Danny Klein
Intern Robotics Engineer specializing in robotics testing, controls, and automation
“Robotics engineering intern and mechanical engineering master’s student who bridges hardware testing and ML/ROS2 software: built a PyTorch model to map motor test data across motor types using electrical specs (Kv/Kt/R/L) and validated it against new motors to meet strict torque/thermal accuracy targets. Also integrated CNN-based perception into ROS2 for real-time navigation and implemented MPC with time-synchronized multi-topic messaging to avoid stale-data control issues.”
Arnav Singh
Junior Software Engineer specializing in full-stack web, cloud data, and applied ML
“Backend engineer who evolved the X-Ray gaming analytics platform, leading a zero-downtime MongoDB→AWS DocumentDB migration with dual-write, checksum-based validation, and Kubernetes canary rollouts while maintaining real-time monitoring for millions of concurrent sessions. Strong in FastAPI/Python API scaling and performance tuning (cut latency from ~2s to <150ms and reduced DB load 90%) plus production-grade auth/RLS security patterns (JWT, Supabase Auth, PostgreSQL RLS).”
Kerui Lu
Intern Software Engineer specializing in cloud, full-stack, and distributed systems
“Interned at SLB and owned an end-to-end GenAI chatbot deployment for a finance team, including invoice PDF data extraction and an LLM-driven layer (LangGraph/LangChain) that translated natural language to SQL and returned results in natural language. Validated LLM JSON outputs against benchmarks using DeepDiff and deployed the solution via Docker to Kubernetes, managing pods with k9s.”
Tianyi Wang
Entry-Level Backend/Cloud Engineer specializing in distributed systems and AI platforms
“Full-stack engineer with deep serverless AWS experience who built VidToNote, an AI video analysis platform, end-to-end using Next.js App Router/TypeScript and an event-driven pipeline (API Gateway, Lambda, DynamoDB, S3, Step Functions, SQS). Strong on production reliability and observability (CloudWatch, X-Ray, structured logging), plus data/analytics work in Postgres with measurable query optimizations and durable LLM evaluation workflows. Amazon background; integrated 22 AWS services and completed AWS Solutions Architect Professional certification within a month.”
“Software engineer with experience at Amazon and Agora building end-to-end systems: a knowledge-base AI chatbot (React/TypeScript UI + retrieval/response backend + Docker deployment) and an internal approval governance platform using AWS Step Functions and DynamoDB. Emphasizes fast iteration without sacrificing trust via feature-flag rollouts, citation-required answers, abstention on low-confidence retrieval, regression query sets, and strong observability (request IDs, structured logs, latency/error monitoring).”