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Vetted Keras Professionals
Pre-screened and vetted.
KAUSHIK KUMAR KOLAR RAVINDRA KUMAR
Intern-level Software Engineer specializing in AI/ML and time-series forecasting for finance
“Built a production AI-driven QA automation platform using a multi-agent architecture (MCPs + LangGraph) to run parallel website tests across multiple device environments via automated image building and containerization. Currently collaborating with restaurant operators and managers to deliver an agentic restaurant analytics system, emphasizing deep domain discovery with non-technical stakeholders.”
Dinesh Kumar Patibandla
Mid-level Machine Learning Engineer specializing in LLMs and RAG for finance and healthcare
“ML Engineer with recent Goldman Sachs experience building and deploying a production RAG/LLM assistant for summarization, drafting, and internal knowledge retrieval across financial, risk, and compliance documents. Designed for heavy regulatory constraints and scaled to 10,000+ concurrent users using Kubernetes-based orchestration, dynamic LLM routing, and rigorous testing (adversarial prompts, A/B tests, load simulations) with privacy controls like differential privacy.”
Shram Kadia
Mid-level Software Engineer specializing in backend systems, cloud-native apps, and AI platforms
“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”
Janvitha Mandyam
Mid-level GenAI/ML Engineer specializing in LLM applications and RAG systems
“GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.”
Mid-level AI/ML Engineer specializing in computer vision, NLP, forecasting, and GenAI
Mid-level Software Engineer specializing in Embedded Connectivity and AI/ML
Mid-Level Software Engineer specializing in microservices, cloud, and machine learning
Senior Data Scientist specializing in GenAI, fraud/credit risk, and cloud MLOps
Mid-level Machine Learning Engineer specializing in NLP, MLOps, and risk/fraud analytics
Senior Data Scientist specializing in NLP, GenAI, and cloud ML platforms
Mid-level AI/ML Engineer specializing in fraud detection and Generative AI
Mid-level Embedded Systems Engineer specializing in wireless, Linux, and real-time systems
Mid-level AI/ML Engineer specializing in MLOps, NLP/LLMs, and computer vision
Mid-level AI/ML Engineer specializing in fraud detection, risk modeling, and real-time ML systems
Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps
Senior Research Scientist specializing in LLM safety, robustness, and out-of-distribution detection
Junior AI/ML Engineer specializing in Computer Vision and LLM/RAG systems
Mid-level Data Scientist specializing in applied AI, MLOps, and production LLM systems
Mid-level Data Scientist specializing in NLP, LLMs, and predictive analytics
Principal AI/ML Architect & Senior Data Scientist specializing in financial fraud and risk
Mid-level Data Analyst/Data Scientist specializing in product analytics and machine learning