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Vetted Clustering Professionals
Pre-screened and vetted.
Senior Full-Stack Software Engineer specializing in cloud storage and developer tooling
Junior Software Engineer specializing in AI/ML and recommendation systems
Executive Blockchain Analytics Founder/CEO specializing in institutional-grade data platforms
Senior AI/ML Engineering Manager specializing in NLP, computer vision, and MLOps
Senior Full-Stack Developer specializing in cloud-native microservices and AI-driven healthcare apps
Senior Data Engineer specializing in cloud-native data platforms and streaming pipelines
Kalyani Chittipolu
Mid-level Data Engineer specializing in AI/ML platforms and cloud data pipelines
“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”
“JavaScript/TypeScript engineer from Ridgeline who built a retry feature for failed staging-to-production promotions with pre-promotion health checks. Brings a backend-scaling mindset to runtime performance work (metrics-first bottlenecking, Big-O analysis, async/parallelism, caching) and leverages Cursor/AI tooling to ramp quickly on large codebases.”
Mid-level Data Scientist specializing in NLP, MLOps, and semiconductor manufacturing analytics
Mid-level Machine Learning Engineer specializing in search ranking and NLP
Senior Data Scientist specializing in NLP, LLMs, and Generative AI automation
Intern Software Engineer specializing in data engineering and LLM evaluation
Senior AI/ML Engineer & Data Scientist specializing in NLP, entity resolution, and knowledge graphs
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.”
Intern Machine Learning Engineer specializing in LLMs, RAG, and model quantization
Principal Machine Learning Scientist specializing in GenAI, LLMs, and RAG
Mid-level Data Scientist specializing in ML for healthcare and strategy analytics
MARCUS JOHNSON
Senior AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”
Mid-level AI/ML Engineer specializing in NLP/LLMs and production ML systems
Intern AI/ML Engineer specializing in LLM agents, RAG, and computer vision