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Vetted FAISS Professionals
Pre-screened and vetted.
Senior AI/ML Engineer specializing in NLP, LLMs, and retrieval systems
Kaiqi Zhang
Senior Full-Stack Engineer specializing in cloud-native SaaS and AI applications
“ML/LLM engineer with hands-on experience shipping production RAG systems at Google Clinical Search and GenAI recommendation/summarization features in Meta Ads. Stands out for combining research-to-production execution with rigorous grounding, evaluation, safety checks, and reusable Python platform components that improved both reliability and team velocity.”
Senior AI Engineer specializing in LLMs, generative AI, and ML systems
Staff Machine Learning Engineer specializing in LLMs and Generative AI
Staff AI Systems Engineer specializing in LLM platforms and distributed systems
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Senior AI Engineer specializing in NLP and large language models
Senior AI/ML Engineer specializing in LLM applications, RAG systems, and MLOps
Senior Machine Learning Engineer specializing in Generative AI and NLP
Chase Bradley
Staff AI Engineer specializing in LLM systems, retrieval, and ML infrastructure
“ML/LLM engineer from Cohere who has owned retrieval, reranking, agentic workflows, and internal evaluation infrastructure end-to-end in production. Particularly strong in turning brittle RAG and research-heavy ideas into scalable enterprise systems with grounded outputs, lower customer escalations, and adoption by major clients like Notion and Fujitsu.”
Christopher Sipola
Senior Machine Learning Engineer specializing in LLMs and recommendation systems
“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”
Esha Pahwa
Intern Machine Learning Engineer specializing in LLM agents and multimodal reasoning
“LLM/agent engineer who built a production code-generation agent at Corvic AI that lets non-technical users query CSV/tabular data in natural language by generating and executing Python. Focused on making LLM systems reliable and scalable via schema-aware validation, sandboxed execution-feedback retries, prompt caching/embeddings, async execution, and high-throughput data processing with Polars; also partnered with Adobe product/marketing to ship brand-aligned AI content generation for email and push notifications.”
Sudheer Bommichetty
Mid-level Machine Learning Engineer specializing in NLP, MLOps, and Generative AI
“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”
Pradeep Nadella
Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling
“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”
Muneendra M
Mid-level Software Engineer specializing in event-driven backend and AI-enabled systems
“Full-stack engineer at Stripe who owned a webhook monitoring and retry platform end-to-end, spanning backend services, React dashboards, and production operations. Stands out for combining strong distributed-systems judgment with product polish, including a reported 31% improvement in webhook delivery reliability and UI improvements that reduced support burden.”
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Senior Software Engineer specializing in cloud-native microservices and real-time systems
Senior AI Full Stack Engineer specializing in generative AI and ML systems
Senior Machine Learning Engineer specializing in NLP and Generative AI