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Vetted seaborn Professionals
Pre-screened and vetted.
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Staff Data Scientist specializing in machine learning, deep learning, and big data
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Executive AI/ML Engineer specializing in LLMs, NLP, and production ML systems
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.”
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Senior Strategy & Operations Leader specializing in AI, analytics, and growth strategy
Senior AI/ML Engineering Manager specializing in NLP, computer vision, and MLOps
Mid-level Data Scientist specializing in Generative AI and LLM applications
Jayaprakash Majji
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference
“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”
Brian Gomez
Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision
“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”
Deepak Guntreddi
Mid-level Full-Stack Developer specializing in Java/Spring Boot and React
“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
Senior Data Scientist / ML Engineer specializing in LLMs, generative AI, and MLOps
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and scalable inference