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Vetted SciPy Professionals
Pre-screened and vetted.
Senior Data Scientist specializing in machine learning and battery R&D analytics
Staff-level Full-Stack Python Engineer specializing in AI/ML and cloud platforms
Junior Software Developer specializing in Python, data engineering, and GenAI
Mid-level Data Scientist specializing in NLP, computer vision, and MLOps
Mid-level AI/ML Engineer specializing in LLM agents, search/recommendation, and MLOps
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Mid-level Software Engineer specializing in AI/GenAI and cloud-native backend systems
Senior Python Engineer specializing in scalable backend and AI-enabled web platforms
Staff Software Engineer specializing in Python APIs and AWS-native data platforms
Junior Full-Stack Python Developer specializing in cloud-native web applications
Intern Data Scientist / ML Engineer specializing in predictive modeling and data pipelines
Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP
Mid-level Data Analyst specializing in marketing analytics and machine learning
Swarag Reddy Pingili
Junior AI/ML Software Engineer specializing in LLM agents and RAG systems
“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”
Swapnil Ramanna
Mid-level Data Scientist specializing in Generative AI and Healthcare Analytics
“Built a LangGraph-based, tool-routing LLM chatbot to deliver fast, trustworthy investment-stock insights (including tariff impact) and deployed it to production on Snowflake after initially developing in Azure with AI Search and the Microsoft Agent Framework. Improved routing robustness by moving from LLM-based decisions to a deterministic router backed by schema-relationship graphs and YAML metadata, and ran the project iteratively with non-technical stakeholders over an 8-month engagement.”