.png){kind=logo}
Vetted Regression Analysis Professionals
Pre-screened and vetted.
Junior Machine Learning Engineer specializing in Generative AI and MLOps
Mid-level AI Product Engineer and Data Analyst specializing in LLM automation
Junior Data & BI Analyst specializing in analytics engineering, NLP, and financial risk analytics
Mid-level financial and data analyst specializing in underwriting and business analytics
Junior Machine Learning Engineer specializing in scalable ML systems and LLMs
Mid-level AI/ML Engineer specializing in risk modeling, healthcare analytics, and MLOps
Intern Data Scientist and GenAI Software Engineering specializing in ML and LLM evaluation
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Vishesh Patel
Junior AI/ML Engineer specializing in Python ML, NLP, and model deployment
“Built and productionized a real-time social-media sentiment analysis system used by a marketing team to monitor brand/campaign performance. Experienced in orchestrating LLM workflows with LangChain (validation → prompting → parsing → post-processing), plus monitoring, retraining, and RAG-style retrieval using embeddings/vector stores to keep outputs reliable over time.”
Balakrishna Mylapilli
Mid-level AIML Engineer specializing in production ML and MLOps
“ML practitioner who built a production customer risk scoring system to replace slow manual approvals, owning the full pipeline from feature engineering and XGBoost training to deploying a Dockerized FastAPI prediction service. Emphasizes reliability and business-aligned evaluation (recall/ROC-AUC, threshold tuning, drift monitoring) and is comfortable translating model decisions into stakeholder metrics like conversion rate (experience at EasyBee AI).”
Vaibhavi Madhav Deshpande
Mid-level AI Engineer specializing in LLM agents, RAG, and data pipelines
“Built and productionized LLM-powered workflows that generate contextual insights from structured financial data, including prompt/retrieval design, data standardization, and reliability controls like rate limiting and batching. Also diagnosed and fixed real-time failures in an automated order validation system using logs/metrics, staging reproduction, edge-case handling, retries, and alerting, while supporting sales/customer teams with demos, scripts, and FAQs to drive adoption.”
Yasaswini Majety
Intern AI/ML Engineer specializing in LLMs, RAG, NLP, and MLOps
“Built and deployed a production RAG-based internal document Q&A system using LangChain, vector search, and a dockerized FastAPI LLM service. Focused on reliability by systematically reducing hallucinations and improving retrieval through prompt grounding/abstention strategies, chunking and top-k tuning, and iterative evaluation with logged metrics and manual validation.”
Jeet Choksi
Mid-level Machine Learning Engineer specializing in real-time AI and data platforms
“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”
Mid-level Machine Learning Engineer specializing in NLP and LLM evaluation
Junior Data Analyst & Business Analyst specializing in BI, analytics, and process optimization
Intern Data Scientist specializing in LLM agents, RAG, and real-time ML pipelines
Mid-level Data Scientist specializing in computer vision and behavioral analytics
Junior AI/ML Engineer specializing in LLMs, RAG, and applied NLP
Entry-Level Data Scientist specializing in machine learning, NLP, and cloud analytics
Mid-level AI/ML Engineer specializing in LLM agents, RAG pipelines, and AI automation
Junior Machine Learning Engineer specializing in LLMs and multimodal AI