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Vetted XGBoost Professionals
Pre-screened and vetted.
Senior Full-Stack AI/ML Engineer specializing in personalization, NLP, and GenAI platforms
Mid-level AI/ML Engineer specializing in Generative AI agents and enterprise analytics
Mid-level Data Analyst and Business Analyst specializing in BI, reporting, and analytics
Mid-level Data Analyst specializing in financial analytics and regulatory reporting
Senior AI/ML Engineer specializing in computer vision, GenAI, and 3D spatial analytics
Senior Machine Learning Engineer specializing in AI, NLP, computer vision, and GenAI
Mid-level Software Engineer specializing in full-stack FinTech and AI systems
Mid-level AI/ML Engineer specializing in Generative AI and fraud detection
Senior Data Scientist specializing in healthcare analytics and scalable ML pipelines
Mid-level GenAI/ML Engineer specializing in LLMs, RAG, and agentic AI
Anshul Joshi
Mid-Level Software Engineer specializing in distributed systems and GenAI
“Capgemini engineer with 4+ years building and deploying high-availability, low-latency fraud detection APIs and multi-cluster distributed systems for a Fortune 20 bank, including zero-downtime production rollouts and multi-layer (SQL/network/hardware) performance debugging. Also built a Python + OpenAI/LangChain LLM-powered grading workflow for Austin School for Women, cutting feedback time from 90 minutes to 5 minutes per submission for 200+ learners.”
Senior Machine Learning Engineer specializing in AI systems, LLMs, and MLOps
Nightvid Cole
Senior Computer Vision & Sensor Algorithms Engineer specializing in imaging systems
“Robotics/remote-sensing software engineer who built and validated multisensor image-processing and spectral chemical-detection pipelines (RX anomaly detection, ACE), including calibration protocols with a motorized shutter and rigorous data QC. Uses white-box NumPy simulators to debug SLAM/registration issues before translating logic to C++, and partnered with hardware teams to solve temperature-driven signal variation via combined software calibration and improved thermal management.”
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems
Senior Machine Learning Engineer specializing in MLOps and Generative AI
Mid-level Data Scientist specializing in financial ML, NLP, and MLOps
Jayeetra Bhattacharjee
Mid-level AI/ML Engineer specializing in LLMs, NLP, and analytics automation
“AI/ML Engineer (TCS) who built and deployed a production LLM-powered audit transaction validation service to reduce manual review of unstructured transaction records and comments. Implemented a LangChain/Python pipeline for extraction/normalization and discrepancy detection, with strong production reliability practices (decision logging, dashboards, labeled eval sets) and a human-in-the-loop auditor feedback loop to improve precision/recall under strict data-sensitivity and near-real-time constraints.”
Rithindatta Gundu
Mid-level AI/ML Engineer specializing in LLM systems and cloud MLOps
“Built a production LLM-powered fraud detection platform at Wells Fargo, combining OpenAI/Hugging Face models with RAG-based explanations to make flagged transactions interpretable for risk and compliance teams. Delivered low-latency, real-time inference at high scale on AWS (SageMaker + EKS), with strong observability and security controls, reducing manual reviews and false positives in a regulated environment.”
Naga Gayatri Bandaru
Mid-level AI/ML Engineer specializing in MLOps and production ML systems
“Backend/ML engineer who has shipped high-scale real-time systems across e-commerce and healthcare: built a PharmEasy real-time recommendation engine for ~2M monthly users (cut feature latency 5 min→30 sec; +15% cross-sell) and architected a HIPAA-compliant multimodal clinical diagnostic workflow (DICOM+EHR) with XAI, MLOps (MLflow/Airflow/K8s), and drift/monitoring guardrails supporting 10k+ daily predictions.”