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Vetted Keras Professionals
Pre-screened and vetted.
Senior Machine Learning Engineer specializing in LLMs, agentic AI, and MLOps
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and AI personalization
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and deep learning
Principal Software Engineer specializing in enterprise AI/ML and multi-cloud architecture
Mid-level Data Engineer specializing in cloud data pipelines and analytics platforms
Junior Software Engineer specializing in AI/ML and FinTech systems
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-Level Full-Stack Software Engineer specializing in FinTech and AI risk scoring
Mid-level Full-Stack Developer specializing in FinTech and fraud detection
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Executive Engineering Leader specializing in Telehealth Platforms and Healthcare IT
Hari Kiran Reddy Rommala
Mid-Level Full-Stack Software Engineer specializing in cloud-native data platforms
“LLM/agentic systems practitioner who specializes in moving customer prototypes into production within microservices environments, emphasizing reliability, latency, security, and measurable success metrics. Experienced in real-time troubleshooting using logs/traces and in enabling adoption through hands-on developer workshops (including live coding in Java Spring Boot) and pre-sales POCs that address technical objections and integration risk.”
Alp Komban
Junior Machine Learning Engineer specializing in computer vision for medical imaging
“Applied ML/LLM practitioner working in healthcare-facing products, using RAG and LoRA fine-tuning on medical data and implementing production monitoring (confidence scoring) for clinician oversight. Has hands-on experience debugging agentic/LLM pipelines (including OCR preprocessing fixes) and regularly delivers technical demos to doctors, investors, and conferences—contributing to adoption and even helping close a funding round through end-to-end pipeline walkthroughs.”
Akash Patil
Mid-Level Software Engineer specializing in backend systems and LLM/RAG applications
“Backend/AI engineer at Intuit who built a production AI-powered case assistant for support agents (FastAPI on AWS EKS) combining Postgres case data, OpenSearch retrieval with embedding reranking, and internal LLMs. Improved peak-season reliability by diagnosing P95/P99 timeout spikes and cutting P95 latency from ~800ms to <400ms via composite indexing, keyset pagination, connection pool tuning, and caching, while adding grounded-generation guardrails (evidence packs, confidence thresholds, fallbacks, human-in-the-loop).”
Haider Shah
Principal AI/ML Architect specializing in GenAI, LLMs, RAG, and Agentic AI
“FinTech/AI engineer who has shipped an end-to-end discrepancy-detection product for financial managers using Next.js, FastAPI/GraphQL, Pinecone, and AWS (with dev/staging/prod, observability, A/B testing, and documentation). Also built an AI-native “AI Genesis” system with agentic cyclic workflows, routing, and tool use, and has experience modernizing legacy systems via the strangler fig pattern while coordinating with senior stakeholders on a 5G autonomous simulation platform.”
Sayuj Shah
Mid-level Data Analyst & AI Practitioner specializing in ML, LLMs, and analytics platforms
“Data Analyst at U.S. Cellular who built production LLM solutions, including a Tableau-embedded chatbot that converts natural language questions into Oracle SQL and returns actionable KPI insights for non-technical users. Also authored MAD-CTI, a multi-agent LLM system for dark web hacker forum threat intelligence (published in IEEE Access) that outperformed single-agent approaches by 14%.”