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Vetted Azure Machine Learning Professionals
Pre-screened and vetted.
Director-level AI/ML Technology Leader specializing in healthcare and life sciences
Mid-level AI/ML Engineer specializing in GPU-accelerated LLMs, RAG, and production MLOps
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and multi-agent systems
Senior AI/ML Software Engineer specializing in LLMs, NLP, and scalable ML platforms
Senior Data Scientist specializing in Generative AI and LLM evaluation
Senior Machine Learning & GenAI Engineer specializing in LLM systems and data pipelines
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems
Mid-level Technical Solutions Architect & Technical Operations Manager specializing in AI automation
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Senior Software Engineer specializing in cloud platforms, data pipelines, and ML
Senior Data Scientist specializing in large-scale ML systems and recommendations
Parth Vadera
Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps
“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”
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.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and distributed MLOps
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps
Staff Data Scientist / AI-ML Engineer specializing in fraud detection, NLP, and recommendations
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.”
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.”