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Vetted Machine Learning Engineers in California
Pre-screened and vetted in California.
Soma Meghana Prathipati
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
“ML/robotics engineer with Apple experience who built a computer-vision-driven industrial defect detection system integrating a robotic arm with ROS-based real-time inference on an edge GPU. Drove major performance gains (cut inference time ~60% via quantization + TensorRT) and improved robustness to lighting/material variation, with strong emphasis on production reliability (health checks, watchdogs, observability, CI/CD) and interest in shaping early-stage startup engineering culture.”
Senior Machine Learning Engineer specializing in NLP, LLMs, and scalable ML platforms
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
Mid-level Machine Learning Engineer specializing in real-time fraud detection and edge AI
Junior Software Engineer specializing in LLMs, Agentic AI, and MLOps
Mid-level Machine Learning Engineer specializing in reinforcement learning and multimodal AI
Mid-level AI/ML Engineer specializing in LLM RAG pipelines and cloud MLOps
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Mid-level AI/ML Engineer specializing in LLM, RAG, and multimodal systems
Senior Machine Learning Engineer specializing in AI platforms and backend systems
Senior AI/ML Engineer specializing in healthcare and fintech AI systems
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Senior Applied AI Engineer specializing in LLMs, RAG, and computer vision
Chanakya rudru
Senior Machine Learning Engineer specializing in conversational AI and Generative AI
“ML/AI engineer with experience at Uber and Scale AI, focused on customer service automation across both classical NLP and generative AI systems. Has owned systems from experimentation through production on AWS, including LLM fine-tuning, RAG optimization, safety evaluation, and internal Python platform tooling that improved consistency and engineering velocity.”
Kella Dhanush Venkata Sai
Junior ML Engineer specializing in Generative AI and LLM applications
“Built a production internal knowledge assistant using a RAG pipeline over large spreadsheets, PDFs, and support documents, using transformer embeddings stored in FAISS. Focused on real-world production challenges—format normalization, retrieval quality, hallucination reduction (context-only + citations), and latency—using hybrid retrieval, quantization, and containerized deployment, and communicated the workflow to non-technical stakeholders using simple analogies.”
Chappidi Sasi
Mid-level Machine Learning Engineer specializing in GPU-accelerated LLM training and inference
“ML/LLM engineer with production experience building a multi-GPU LLM inference platform using TensorRT and vLLM, achieving ~40% p95 latency reduction through batching/KV caching, quantization, and CUDA/runtime tuning. Also has end-to-end orchestration experience (Kubernetes, Airflow) and has delivered real-time fraud detection systems at Accenture in close collaboration with non-technical risk and product stakeholders.”
Mid-level Machine Learning Engineer specializing in deep learning, MLOps, and real-time inference
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in MLOps, real-time ML, and LLM/RAG systems
Senior Full-Stack Engineer specializing in AI, cloud platforms, and enterprise systems