.png){kind=logo}
Vetted Hyperparameter Tuning Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and cloud-native MLOps
Mid-level AI/ML Engineer specializing in financial risk, fraud analytics, and MLOps
Senior Data Scientist specializing in NLP, anomaly detection, and recommender systems
Mid-level Data Scientist specializing in NLP, deep learning, and Generative AI
Mid-level Data Scientist specializing in NLP, predictive analytics, and healthcare/enterprise SaaS
Junior Data Scientist specializing in NLP, OCR, and recommendation systems
Mid-level Data Scientist specializing in LLMs and applied machine learning
Mid-level Machine Learning Engineer specializing in healthcare risk prediction and GenAI
Mid-level Machine Learning Engineer specializing in forecasting, NLP, and MLOps
Mid-level Machine Learning Engineer specializing in Generative AI, NLP, and recommender systems
Mid-level Machine Learning Engineer specializing in MLOps and LLM/RAG systems
Mid-level Data Scientist specializing in ML, NLP, and forecasting across finance and retail
Senior AI/ML Engineer specializing in MLOps and Generative AI (LLMs/RAG)
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Bharath Reddy Nallu
Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps
“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”
Rodolfo Lopez
Senior Math Educator transitioning to Data Science & Business Analytics
“Recent McCombs School of Business (UT Austin) Post Graduate Program graduate in Data Science & Business Analytics with hands-on project experience spanning stock clustering/segmentation and hotel booking-cancellation prediction. Strong in end-to-end analysis workflows (EDA, cleaning, feature engineering) and rigorous model comparison/selection, with exposure to boosting methods and imbalanced-data techniques; limited experience so far with embeddings/vector databases and production deployment.”