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Vetted Machine Learning Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in backend, full-stack, and network automation
Mid-Level Software Engineer specializing in distributed systems and cloud platforms
Mid-Level Low-Code Developer specializing in Dynamics 365 and Power Platform
Senior Engineering Director specializing in Generative AI, XR, and gaming platforms
Mid-level Machine Learning Engineer specializing in LLMs, Generative AI, and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Senior Data Scientist and Machine Learning Researcher specializing in NLP, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in Generative AI and RAG assistants
Principal Enterprise Solutions Architect specializing in AI & data platforms
Junior Software Engineer specializing in backend, microservices, and cloud
Senior QA Engineer specializing in game and interactive application testing
Senior Full-Stack Software Engineer specializing in Python, React, and LLM-powered applications
Dhruv Kamalesh Kumar
Mid-level Generative AI Engineer specializing in LLM agents and RAG applications
“GenAI builder and technical lead with ~2 years of hands-on production experience, including GENIE (a GenAI sandbox for ~44,000 Massachusetts public-sector employees) and A-IEP, a multilingual platform helping parents understand complex IEP documents (cut processing from ~15 minutes to ~2 and used by 1,000+ parents). Strong in RAG/agentic architectures, AWS serverless + Step Functions orchestration, and rigorous evaluation/guardrails for reliable real-world deployments.”
Sahil Gupta
Junior AI Software Engineer specializing in LLM agents, RAG, and healthcare NLP
“Backend engineer who built an agentic LLM system for private equity/finance that answers questions over enterprise contracts and documents using a vector-db RAG pipeline. Differentiator is a trust-focused citation framework (with highlighted source text) to reduce hallucinations in high-stakes workflows, plus strong DevOps experience deploying microservices on Kubernetes with Helm/GitOps and building Kafka real-time pipelines.”
Himanshu Kiran Garud
Mid-level Software Engineer specializing in full-stack systems and applied AI
“Backend/ML engineer who has built both enterprise data pipelines and real-time AI products: modular Python (Flask/FastAPI) services integrating automation scripts and low-latency ML inference (MediaPipe, PyTorch) plus OpenAI-powered feedback. Demonstrated measurable performance wins (~30% faster HR workflows; ~40% faster AWS pipelines across 100+ Oscar Health feeds) and strong multi-tenant/data-isolation patterns (schema-based isolation, RBAC, microservices).”
Tanweer Ashif
Mid-level AI/ML Engineer and Data Scientist specializing in LLMs and MLOps
“Data science/AI intern at University at Buffalo Business Services who built and deployed production systems spanning classic ML and LLM assistants. Delivered real-time competitor intelligence for a Cornell-partnered, $1B beverage launch by scraping/cleaning 5,000+ SKUs and deploying models via API, then built a domain-aware LLM assistant to modernize Excel-based workflows with strong grounding, privacy controls, and sub-5s latency.”
Nash Boisvert
Senior Full-Stack Software Developer specializing in web, mobile, and cloud platforms
“Frontend engineer who built a live sports games hub end-to-end: ingesting and normalizing data from 4 external APIs, populating a high-volume live table, and delivering a real-time WebSocket-driven React/TypeScript dashboard. Strong on scalable architecture (SOLID, layered design, queues), performance/load testing with Docker, and startup-style ownership across code review, QA, and staged rollouts to web and app stores.”