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Vetted Amazon SageMaker Professionals
Pre-screened and vetted.
Senior Full-Stack Engineer specializing in AI, Web3, and scalable web platforms
Staff Full-Stack Engineer specializing in data engineering and real-time event platforms
Senior Full-Stack Engineer specializing in cloud, real-time data, and web platforms
Senior Software Engineer specializing in full-stack platforms and AI-driven healthcare systems
Senior Machine Learning Engineer specializing in LLM inference and GPU infrastructure
Senior Software Engineer specializing in healthcare IT and EHR interoperability
Staff Software Engineer specializing in FinTech and scalable distributed systems
Senior Full-Stack Software Engineer specializing in large-scale streaming platforms
Mid-level Machine Learning Engineer specializing in generative AI, NLP, and MLOps
Mid-level AI/ML Engineer specializing in LLM training, RAG, and low-latency inference
Senior Machine Learning Engineer specializing in GenAI, NLP, and recommendation systems
Senior Software Engineer specializing in AI backend platforms and FinTech systems
Director-level Software Development Manager specializing in large-scale cloud platforms
Akshat Shah
Entry-level Software Engineer specializing in full-stack and AI systems
“Frontend-leaning full-stack engineer who described owning an artist search and detail experience across UI, backend integrations, and data modeling. They show practical strength in scalable React architecture, TypeScript safety, and performance tuning, with a product-minded approach to shipping 0→1 features quickly and iterating after launch.”
Christopher Bun
Executive AI/ML technology leader specializing in healthcare, biotech, and legal AI
“Repeat founder and startup advisor with experience spanning academic, health tech, legal tech, sports, and gaming. Has participated in fundraising and due diligence and has built companies, engineering teams, and software platforms from scratch, with a strong product-design-first approach to product-market fit and market selection.”
Arun Ganesh
Junior Software Engineer specializing in healthcare AI and cloud infrastructure
“Amazon Health AI engineer who has owned both full-stack clinical product features and production LLM systems end to end. Built HIPAA-compliant GraphQL and agentic RAG architectures for provider workflows across 125,000+ patients, with measurable impact including 30% higher clinical relevance, 55% lower lookup time, and 12% less false medical information.”
Kenil Tanna
Staff-level Machine Learning Engineer specializing in LLMs and MLOps for Financial Services
“Machine learning/NLP practitioner at J.P. Morgan who led development of a production RAG system and an entity resolution pipeline for complex financial data. Deep hands-on experience with embeddings (Sentence-BERT), vector search (FAISS/pgvector), LLM fine-tuning (LoRA/PEFT), and rigorous evaluation (human-in-the-loop + A/B testing) backed by strong MLOps on AWS (Docker/Kubernetes, MLflow, Prometheus/Datadog).”
Nishitha Thummala
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference
“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”
Nikhil Reddy
Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms
“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”