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Vetted FAISS Professionals
Pre-screened and vetted.
Mid-level Data Engineer specializing in cloud lakehouse and streaming platforms
Mid-level AI/ML Engineer specializing in Generative AI agents and enterprise analytics
Senior AI/ML Engineer specializing in computer vision, GenAI, and 3D spatial analytics
Senior Machine Learning Engineer specializing in AI, NLP, computer vision, and GenAI
Mid-level Software Engineer specializing in GenAI and distributed systems
Senior AI/ML Engineer specializing in Generative AI and conversational systems
Junior Full-Stack Engineer specializing in AI agents, RAG, and distributed systems
Senior Full-Stack Engineer specializing in cloud-native Java microservices and GenAI
Mid-level GenAI/ML Engineer specializing in LLMs, RAG, and agentic AI
Rafael Ortega
Senior Full-Stack & AI Engineer specializing in LLM integrations and cloud-native systems
“Backend/data engineer with hands-on production experience building FastAPI Python APIs and AWS-native platforms (Lambda/API Gateway, SQS, ECS Fargate) with Terraform + GitHub Actions CI/CD and strong reliability practices (JWT/RBAC, retries/timeouts, structured errors/logging). Also built AWS Glue ETL pipelines (S3/RDS to curated S3/Athena) with schema evolution and data quality controls, modernized legacy processing via parallel-run validation and phased cutovers, and has demonstrated SQL tuning impact (seconds to <200ms) plus incident ownership for batch pipeline SLAs.”
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems
Senior Machine Learning Engineer specializing in MLOps and Generative AI
Krishnapriyanka Ponnaganti
Mid-level AI/ML Engineer specializing in agentic AI and production ML systems
“ML/AI engineer with hands-on experience shipping production computer vision and GenAI systems, including a fabric defect detection platform that combined vision models with agentic LLM workflows to reach 89% human-inspector agreement at 200 ms latency. Also built a RAG-based code QA tool for developers and emphasizes production monitoring, evaluation, caching, and reusable Python service design.”
Rithindatta Gundu
Mid-level AI/ML Engineer specializing in LLM systems and cloud MLOps
“Built a production LLM-powered fraud detection platform at Wells Fargo, combining OpenAI/Hugging Face models with RAG-based explanations to make flagged transactions interpretable for risk and compliance teams. Delivered low-latency, real-time inference at high scale on AWS (SageMaker + EKS), with strong observability and security controls, reducing manual reviews and false positives in a regulated environment.”