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Vetted Machine Learning Engineers in California
Pre-screened and vetted in California.
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and multi-agent systems
Mid-level AI/ML Engineer specializing in LLMs, search ranking, and multimodal ML
Junior AI/ML Engineer specializing in LLM agents, RAG, and multimodal data pipelines
Senior Machine Learning & GenAI Engineer specializing in LLM systems and data pipelines
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Senior AI/ML Engineer specializing in computer vision, NLP, and real-time forecasting
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Mid AI/ML Engineer specializing in LLMs, RAG, and multimodal 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.”
Vinay Ramrupe
Mid AI/ML Engineer specializing in LLM and enterprise generative AI
“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and distributed MLOps
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps
Senior Python Developer specializing in AI/ML and cloud-native microservices
Senior Machine Learning Engineer specializing in LLM inference and GPU infrastructure
Mid-level AI/ML Engineer specializing in FinTech risk and fraud systems
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.”