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Vetted pandas Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in backend and data systems
Mid-level Python Backend Developer specializing in FinTech and ML-driven fraud detection
Senior Full-Stack Engineer specializing in backend systems and cloud-native microservices
Mid-level Full-Stack Engineer specializing in Python microservices and cloud automation
Mid-level Robotics & Firmware Engineer specializing in continuum robotics and SerDes validation
Junior AI/ML Engineer specializing in agentic AI and cloud optimization
Mid-level Software Development Engineer specializing in backend systems and ML platforms
Mid-level AI/ML Engineer specializing in recommendation, retrieval, and MLOps
Mid-level Business Analyst specializing in data analytics and enterprise reporting
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Senior Software Engineer specializing in data engineering, BI analytics, and AI/ML
Junior AI/ML Engineer specializing in LLM agents and full-stack AI systems
Senior AI Infrastructure & Backend Engineer specializing in LLM systems
Senior AI Infrastructure Engineer specializing in LLM systems and real-time ML platforms
Peeyush Dyavarashetty
Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems
“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”
Pavan Devulapalle
Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development
“Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).”
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”
Nehal Mahankali
Mid-level Full-Stack Python Developer specializing in cloud-native banking applications
“Backend engineer who built a low-latency real-time transaction API in Python/Flask, with strong depth in PostgreSQL/SQLAlchemy performance tuning (time-based partitioning, indexing, connection pooling). Has production experience integrating ML scoring and OpenAI-style APIs with safety/latency controls, and designing multi-tenant isolation strategies including per-tenant pooling/caching and premium-tenant isolation.”