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Vetted Regression Analysis Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLM agents, search/recommendation, and MLOps
Mid-level Data Scientist specializing in ML, NLP and forecasting
Junior Data Scientist specializing in machine learning and analytics
Mid-level Machine Learning Engineer specializing in MLOps and multimodal AI
Junior Generative AI Engineer specializing in LLM fine-tuning and RAG pipelines
Mid-level AI Engineer specializing in NLP, LLM fine-tuning, and RAG systems
Junior Business Analyst specializing in data analytics and customer behavior insights
Junior Data Analyst specializing in risk analytics and ETL automation
Junior Data Analyst specializing in SQL, Python, and BI analytics
Mid-level Applied AI Engineer specializing in LLMs, Prompt Engineering, and RAG
Mid-level AI/ML Engineer specializing in Generative AI and cloud MLOps
Mid-level Software Engineer specializing in backend systems for Insurance and Healthcare
Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP
Mid-level Data Analyst specializing in marketing analytics and machine learning
Maneesh Ujji
Junior Machine Learning & Data Science professional specializing in AI agents and applied ML
“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”
Helly Shah
Junior Data Analyst specializing in business analytics and machine learning
“Analytics-focused candidate with hands-on project experience in SQL data preparation and Python-based churn modeling. They demonstrated a practical approach to turning messy multi-source data into reporting tables, validating data quality rigorously, and translating churn insights into targeted retention strategies.”
Abhish Khanal
Senior Robotics Researcher specializing in Embodied AI and learning-augmented planning
“Robotics software engineer with experience spanning safety-critical embedded medical hardware (low-cost neonatal baby warmer with PID temperature regulation) and advanced multi-robot planning research (belief-space planning with abstraction + MCTS to handle uncertainty). Strong ROS/ROS2 practitioner (Nav2/SLAM Toolbox/MoveIt) who builds custom packages (e.g., Insta360 panoramic imaging) and is hands-on debugging real robots from SLAM/frontier exploration to multi-robot collision avoidance and real-time performance.”
Ainesh Gunturu
Junior Data Analyst specializing in marketing analytics and machine learning
“Built and deployed a production LLM-assisted recommendation and insights platform that unifies structured, semi-structured, and unstructured data via a modular ingestion pipeline, canonical schemas, embeddings, and late-fusion modeling. Experienced in operationalizing ML/LLM systems with Airflow and Kubernetes (Dockerized services, autoscaling, rolling updates) and emphasizes reliability through layered testing, guardrails, monitoring, and A/B experimentation while partnering closely with non-technical stakeholders.”