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Vetted SHAP Professionals
Pre-screened and vetted.
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 Agentic AI & Backend Engineer specializing in LLM platforms and multi-agent systems
Senior AI/ML Engineer & Data Scientist specializing in NLP, entity resolution, and knowledge graphs
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems
Mid-level Machine Learning Engineer specializing in LLM personalization and scalable MLOps
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Senior Full-Stack Engineer specializing in FinTech and fraud/risk systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
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 Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps
Mid-level AI/ML Engineer specializing in LLM training, RAG, and low-latency inference
Krishna Reddy
Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants
“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”
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.”