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Vetted LightGBM Professionals
Pre-screened and vetted.
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLMs, RAG, and recommendations
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 AI/ML Engineer specializing in Generative AI agents and FinTech risk systems
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Intern Machine Learning Engineer specializing in LLM systems and recommendation/search
Senior Data Scientist specializing in large-scale ML systems and recommendations
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
Mid AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior Machine Learning Scientist specializing in LLMs, RAG, and health AI
Bocheng Wan
Mid-level Software Engineer specializing in consumer robotics and machine learning
“Developer with a structured AI-assisted coding workflow centered on algorithmic rigor, type-safe scaffolding, and spec-driven modular design. Used Claude Code to help build an Android SDK for IPC, quickly ramping up on AIDL and compressing delivery including unit tests from several weeks to two weeks.”
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
Principal Data Scientist specializing in ML, NLP, and forecasting for marketing and supply chain
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Senior Applied AI Engineer specializing in LLMs, NLP, and production AI systems