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Vetted Machine Learning Engineers in California
Pre-screened and vetted in California.
Sushanth Reddy
Senior Machine Learning & GenAI Engineer specializing in LLM systems and data pipelines
Kiriti Golla
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Richard Chiou
Senior AI/ML Engineer specializing in computer vision, NLP, and real-time forecasting
Syam Sundar Akina
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Chetan Panthukala
Mid-level AI/ML Engineer specializing in LLMs, RAG, and distributed MLOps
Sony Arravena
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production NLP
Satish Mattam
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Bharath Mamidi
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps
Yamini Eddala
Senior Python Developer specializing in AI/ML and cloud-native microservices
KEERTHI KOTHA
Senior Machine Learning Engineer specializing in LLM inference and GPU infrastructure
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.”
Kowshika M
Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety
“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”
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.”
Krishna Sahith Poruri
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
“ML/LLM engineer who built a production RAG system (GPT-4 + FAISS + FastAPI) to deliver fast, grounded answers from proprietary documents, optimizing for sub-200ms latency and high-concurrency scale. Strong MLOps/observability background: drift monitoring with Prometheus + Streamlit, automated retraining via Airflow, Kubernetes autoscaling, and MLflow-managed model lifecycle, plus inference cost reduction through quantization and structured pruning.”
Vinnie Yerramadha
Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps
BhanuPrasad Pothagani
Mid-level Full-Stack Java Engineer specializing in scalable microservices and real-time data systems
Thanmayee Reddy
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and on-device ML
Roop Gundu
Mid-level AI/ML Engineer specializing in GPU-accelerated LLM and vision systems
Sravanthi REDDY
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG systems
Hemalatha Papasani
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and GPU-accelerated cloud systems