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Vetted XGBoost Professionals
Pre-screened and vetted.
Junior AI/ML Engineer specializing in NLP, LLM evaluation, and Azure MLOps
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Senior Software Engineer specializing in Python, AI/ML, and AWS cloud-native systems
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems
Mid-level AI/ML Engineer specializing in multimodal and generative AI at scale
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise AI
Mid-level Full-Stack Engineer specializing in Python microservices and cloud automation
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Junior Robotics & AI Engineer specializing in autonomous systems and machine learning
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Senior AI Infrastructure & Backend Engineer specializing in LLM systems
Executive engineering leader specializing in SaaS platform transformation and AI
Senior AI Infrastructure Engineer specializing in LLM systems and real-time ML platforms
Surya Singh
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”