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Vetted PySpark Professionals
Pre-screened and vetted.
Prashanth Kunreddy
Senior AI/Data Engineer specializing in Agentic AI and Advanced RAG on Azure Databricks
“Built production LLM/agent systems for procurement and contract spend controls, including a proactive contract value leakage detection platform that moved an organization from reactive audits to pre-payment rejection. Combines multi-agent orchestration (Semantic Kernel/LangChain/AutoGen), document AI benchmarking (Textract vs Azure DI), and MLOps/testing (MLflow, QTest/Pytest) with strong security practices (RAG-grounded responses to prevent prompt injection). Integrated anomaly alerts directly into SAP SES workflows and Power BI dashboards, citing ~$38M leakage addressed across large spend environments.”
Vamshikrishna Chitturi
Mid-level AI Engineer specializing in Generative AI, LLM fine-tuning, and RAG systems
“Built and deployed production LLM applications including a natural-language-to-read-only-SQL system focused on ambiguity handling and query safety (schema whitelisting, intent validation, confidence checks, deterministic execution). Experienced with LangChain-based, modular agent orchestration and RAG document QA for large PDFs, with a metrics-driven testing/evaluation approach and cross-functional delivery with marketing on an AI content recommendation/search tool.”
Rizwana Shaik
Mid-level Full-Stack Software Engineer specializing in cloud-native apps and AI copilots
“Internship project building and deploying a LLaMA-based, RAG-enabled copilot inside a Professional Services Automation platform, enabling natural-language navigation, text-to-SQL reporting, and project/resource/budget insights across multiple modules. Addressed real production issues like context drift and vague queries with hybrid search, metadata enrichment, and an intent classification/rewriting layer, orchestrated via Apache Airflow—ultimately cutting PMO reporting time by 40%.”
Ahmad Alomari
Senior Data Scientist & Machine Learning Engineer specializing in computer vision and production ML
“PhD in computer engineering who has built production-oriented ML/NLP systems for space-weather prediction using Spark-based ETL on noisy satellite sensor logs. Strong in entity resolution and semantic search—fine-tuned E5 embeddings with contrastive learning and deployed to Pinecone, improving top-5 retrieval precision by 25%—and emphasizes scalable, observable pipelines with Airflow, Docker, and CI/CD.”
Mid-level Machine Learning Engineer specializing in cloud ML pipelines and MLOps
Mid-level Generative AI Engineer specializing in LLMs and RAG for enterprise and FinTech
Senior AI/ML Engineer specializing in Generative AI, NLP, and MLOps
Mid-Level Software Developer specializing in Java, cloud, and full-stack web development
Senior Machine Learning Engineer specializing in computer vision, NLP, and LLM applications
Mid-level Backend Engineer specializing in low-latency FinTech and distributed systems
Mid-level Data Scientist specializing in insurance analytics and machine learning
Senior Full-Stack Developer specializing in Python backends, distributed systems, and AI/ML
Senior Full-Stack Python Engineer specializing in cloud-native web apps and ML
Mid-level Healthcare Data Analyst specializing in public health and clinical research analytics
Mid-level AI/ML Engineer specializing in GenAI, RAG platforms, and ML pipelines
Mid-Level Software Engineer specializing in full-stack development and data/ML systems
Senior Python Developer specializing in FastAPI/Django, AWS, and data/AI platforms
Junior AI Engineer specializing in LLM applications, RAG pipelines, and cloud deployment
Mid-Level Software Engineer specializing in backend systems and ML/LLM pipelines
Junior Machine Learning Engineer specializing in real-time inference and production ML systems
Junior Data Scientist/Analyst specializing in GenAI, RAG, and clinical data platforms
Senior Full-Stack Engineer specializing in SaaS, Healthcare IT, and AI/LLM systems
Junior Data Scientist specializing in production ML, LLM systems, and cloud analytics