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Vetted Neural Networks Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in NLP/LLMs and production ML systems
Junior Software Engineer specializing in backend systems and full-stack development
Senior Robotics Research Scientist specializing in safe, communicative motion planning and ML
Executive Technology Leader specializing in AI, data science, and digital transformation
Junior Robotics Test Engineer specializing in ROS2 autonomous mobile manipulation
Mid-level Software Engineer specializing in AI infrastructure and machine learning
Harsha Kotta
Intern Robotics Researcher specializing in state estimation, SLAM, and sensor fusion
“Robotics software engineering intern at Bell Labs who overhauled indoor mobile robot localization in a ROS 2 stack, combining EKF + particle filtering with a neural network to handle BLE multipath disturbances. Delivered a major accuracy gain (~50 cm to sub-20 cm), earned a company Innovation award, published a paper, and saw the approach adopted across the company’s robot fleet.”
John Bralich
Senior Machine Learning Scientist specializing in generative AI and applied NLP
“ML/AI tech lead who shipped a production LLM workflow at GoDaddy for personalized marketing content, using rich customer context and human-plus-LLM evaluation to drive a statistically significant increase in customers creating posts with GoDaddy tools. Also has experience translating embedding research into a production government RFP search engine, with hands-on optimization of retrieval latency, model size, and deployment reliability.”
Junior Security Engineer specializing in LLM-based incident response and on-chain threat intelligence
Director-level engineering leader specializing in AI-powered cloud-native SaaS platforms
Executive AI Platform & Innovation Leader specializing in Banking, GenAI, and AI Governance
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and real-time recommendation systems
Senior Data Scientist specializing in AI/ML platforms for finance and healthcare
Mid-level Machine Learning Engineer specializing in Bayesian inference and reinforcement learning
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Mid AI/ML Engineer specializing in LLM alignment and scalable AI systems
Ritika Ghosh
Junior Robotics & AI Engineer specializing in ROS2 autonomy and real-time computer vision
“Robotics software engineer from Stanley Black & Decker’s autonomous team who built and deployed a ROS2-based model predictive control system for a commercial autonomous lawn mower, integrating real-time localization, Nav2 planning, and custom control under real-time constraints. Has hands-on field debugging experience (Foxglove, TF timing, covariance/noise tuning) to resolve issues that only appeared outside simulation, plus containerized deployment and CI/CD experience.”
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).”
Suraj Botcha
Intern AI/ML Engineer specializing in LLM systems and industrial AI
“Full-stack AI engineer who has built both document-intelligence products and agentic investigation systems end to end. At ControlRooms.AI, they helped ship a production-facing root cause investigation workflow for industrial operations using Neo4j, FastMCP, RAG, OCR/VLM inputs, and multiple LLMs, contributing to roughly a 10x reduction in manual investigation time. They stand out for designing explainable, traceable AI systems that surface evidence, uncertainty, and missing context rather than forcing overconfident answers.”
“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).”
Likhitha Bethi
Mid-level Software Engineer specializing in backend systems, distributed systems, and applied AI
“Goldman Sachs engineer who owned end-to-end features for an internal onboarding and case management platform, spanning React/TypeScript UI, a GraphQL gateway, and Node + Spring WebFlux microservices. Built and operated a Kafka-based ingestion and search pipeline with DLQs, retries, idempotency, and strong observability, and improved developer experience via backward-compatible GraphQL API design and schema-driven documentation.”