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Vetted PyTorch Professionals
Pre-screened and vetted.
Entry-Level Full-Stack Software Engineer specializing in AI agents and cloud-native apps
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 Generative AI Engineer specializing in LLM, RAG, and multimodal enterprise solutions
Mid-level AI/ML Engineer specializing in Generative AI and RAG assistants
Mid-level Machine Learning Engineer specializing in healthcare and financial AI
Mid-level AI Engineer specializing in LLM agents and production ML systems
Junior Software Engineer specializing in backend, microservices, and cloud
Executive AI Architect specializing in low-power edge/embedded AI systems
Mid-level Software Engineer specializing in backend microservices and FinTech
Mid-level Full-Stack Software Engineer specializing in cloud-native and AI-powered systems
Senior Full-Stack Software Engineer specializing in Python, React, and LLM-powered applications
Sai Krishna Sriram
Mid-level Generative AI & ML Engineer specializing in production LLM and RAG systems
“AI/ML engineer who shipped a production blood-test report understanding and personalized supplement recommendation product, using a LangGraph multi-agent pipeline on AWS serverless with OCR via Bedrock and RAG over vetted clinical research. Also built end-to-end recommender system pipelines at ASANTe using Airflow (ingestion, embeddings/features, training, registry, batch scoring/monitoring) with KPI reporting to Tableau, with a strong focus on safety, evaluation, and measurable reliability.”
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.”