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Vetted Unsupervised Learning Professionals
Pre-screened and vetted.
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
Junior Software Engineer specializing in healthcare data and LLM-powered workflows
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and GPU-accelerated deep learning
Mid-level Machine Learning Engineer specializing in LLM inference and MLOps
Mid-level Data Scientist specializing in GenAI, NLP, and deep learning
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
Mid-level Data Scientist specializing in GenAI, NLP, and deep learning
Mid-level Machine Learning Engineer specializing in recommender systems and LLM/RAG pipelines
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and RAG pipelines
Junior Software Engineer specializing in cloud platforms, microservices, and AI/ML
Senior Data Analytics & Applied ML Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Mid-level AI/ML Engineer specializing in multimodal and generative AI at scale
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Benjamin Kozel
Mid-level Machine Learning & Software Engineer specializing in RAG systems and ML infrastructure
“Built and deployed an in-house RAG LLM system ("MONTY") using LLaMA 3B + FAISS to help teams quickly understand long internal/external specifications. Delivered usable production performance despite severe compute limits (single RTX 3080) by tuning retrieval/reranking and model choice, and is planning a LightRAG/knowledge-graph rewrite to improve accuracy and latency.”
Sri Lekha Kandadai
Mid-level Machine Learning Engineer specializing in MLOps and multimodal AI
“ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.”
Mid-level Machine Learning Engineer specializing in MLOps, computer vision, and generative AI
Junior Robotics & AI/ML Engineer specializing in autonomous systems and computer vision