.png){kind=logo}
Vetted Amazon SageMaker Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in NLP, MLOps, and scalable ML platforms
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
Mid-level Data Scientist specializing in ML, NLP, and production AI workflows
Senior DevOps/Site Reliability Engineer specializing in cloud infrastructure and automation
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Staff-level AI/ML Engineer specializing in enterprise RAG, agentic automation, and AI governance
Mid-level AI/ML Engineer specializing in NLP, LLMs, and MLOps
Senior Data Scientist specializing in ML, fraud risk, and Generative AI (RAG/LLMs)
Mid-level AI/ML Engineer specializing in GenAI, computer vision, and real-time ML pipelines
Senior Full-Stack AI/ML Engineer specializing in personalization, NLP, and GenAI platforms
Mid-level Data Scientist / ML Engineer specializing in LLMs and predictive analytics
Senior Java Full-Stack Developer specializing in cloud-native microservices and FinTech
Executive Engineering Leader specializing in data platforms and SaaS
Senior Data Engineer specializing in cloud data platforms and real-time streaming pipelines
Senior Data Scientist specializing in healthcare analytics and scalable ML pipelines
Anshul Joshi
Mid-Level Software Engineer specializing in distributed systems and GenAI
“Capgemini engineer with 4+ years building and deploying high-availability, low-latency fraud detection APIs and multi-cluster distributed systems for a Fortune 20 bank, including zero-downtime production rollouts and multi-layer (SQL/network/hardware) performance debugging. Also built a Python + OpenAI/LangChain LLM-powered grading workflow for Austin School for Women, cutting feedback time from 90 minutes to 5 minutes per submission for 200+ learners.”
KrishnaVarshith Pabbisetty
Mid-level Backend Software Engineer specializing in Spring Boot, microservices, and cloud-native AI
“Backend engineer with experience modernizing a large-scale procurement platform at Jio Platforms by breaking a monolith serving 35 business units into Spring Boot microservices, improving uptime and cutting report latency ~30%. Also built high-concurrency FastAPI systems (200ms at ~500 concurrent users) with strong security (JWT/OAuth2/RBAC), event-driven Kafka integrations, and reliability patterns like exactly-once delivery for ~1M monthly triggers.”
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems