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Vetted XGBoost Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in GenAI, forecasting, and MLOps
Mid-level Data Scientist/ML Engineer specializing in LLMs, NLP, and recommender systems
Mid-level AI/ML Engineer specializing in LLM, RAG, and multimodal systems
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Mid-level Agentic AI & ML Engineer specializing in LLM agents and RAG systems
Mid-level AI/ML Engineer specializing in cloud MLOps and GenAI for fraud detection
Asrith Velireddy
Mid-level AI/ML Engineer specializing in MLOps, LLMs, and scalable ML systems
“ML/LLM engineer at Adobe who deployed a transformer-based personalization and campaign-targeting recommender system end-to-end, including PySpark/Airflow pipelines processing 12M+ events/day and containerized inference on AWS SageMaker (Docker/Kubernetes). Also has hands-on LLM workflow experience (RAG, semantic search, prompt optimization, hallucination mitigation) with a metrics-driven approach to reliability, drift monitoring, and reproducible retraining via MLflow.”
Kella Dhanush Venkata Sai
Junior ML Engineer specializing in Generative AI and LLM applications
“Built a production internal knowledge assistant using a RAG pipeline over large spreadsheets, PDFs, and support documents, using transformer embeddings stored in FAISS. Focused on real-world production challenges—format normalization, retrieval quality, hallucination reduction (context-only + citations), and latency—using hybrid retrieval, quantization, and containerized deployment, and communicated the workflow to non-technical stakeholders using simple analogies.”
Chappidi Sasi
Mid-level Machine Learning Engineer specializing in GPU-accelerated LLM training and inference
“ML/LLM engineer with production experience building a multi-GPU LLM inference platform using TensorRT and vLLM, achieving ~40% p95 latency reduction through batching/KV caching, quantization, and CUDA/runtime tuning. Also has end-to-end orchestration experience (Kubernetes, Airflow) and has delivered real-time fraud detection systems at Accenture in close collaboration with non-technical risk and product stakeholders.”
Mid-level Machine Learning Engineer specializing in deep learning, MLOps, and real-time inference
Senior Data Engineer specializing in cloud data platforms and large-scale ETL
Mid-level Data Engineer specializing in analytics, BI dashboards, and ETL pipelines
Entry-Level Data Scientist specializing in Applied Analytics and Machine Learning
Junior Machine Learning Engineer specializing in LLMs and retrieval-augmented generation
Mid-level AI/ML Engineer specializing in fraud detection and customer lifetime value modeling
Mid-level Data Scientist specializing in ML, NLP, and fraud/anomaly detection
Mid-level Machine Learning Engineer specializing in LLM inference and MLOps