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Vetted AI & Machine Learning Professionals
Pre-screened and vetted.
Popular Titles
Senior Applied Scientist specializing in LLMs, GenAI systems, and AutoML
Senior Applied ML Scientist specializing in LLMs, ads ranking, and RAG 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
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal recommendation 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 AI/GenAI and cloud-native platforms
Senior AI/ML Engineer specializing in computer vision, NLP, and real-time forecasting
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Intern Machine Learning Engineer specializing in LLM systems and recommendation/search
Intern Machine Learning Engineer specializing in systems, kernels, and GPU computing
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.”
Yishi Wang
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference