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Vetted FAISS Professionals
Pre-screened and vetted.
Senior Machine Learning Engineer specializing in NLP and Generative AI
Senior AI/ML Engineering Manager specializing in NLP, computer vision, and MLOps
Senior AI Engineer specializing in LLM platforms and scientific workflow automation
Software Development Manager specializing in multimodal visual search and AI platforms
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Senior AI/ML Engineer specializing in conversational AI and enterprise LLM systems
Senior AI/ML Engineer specializing in Generative AI and cloud-native platforms
Senior Machine Learning Engineer specializing in Generative AI and NLP
Director of Engineering specializing in AI/ML, GenAI, and cloud platforms
Mid-level Data Scientist specializing in Generative AI and LLM applications
Senior Full-Stack Software Engineer specializing in AI/ML for FinTech & E-commerce
Senior AI/ML Engineer specializing in generative AI and recommendation systems
Mid-level AI/ML Engineer specializing in Generative AI and multilingual NLP
Tolulope Akinlabi
Mid-level Cyber & Cloud Security Analyst specializing in AI/ML and cloud risk
“Built a production AI security compliance assessment system using the OpenAI API that ingests company policy documents, performs RAG over embeddings stored in Supabase/FAISS, and generates executive-level gap and maturity reports mapped to NIST CSF, SOC 2, and PCI DSS. Also developed a multi-agent trading assistant orchestrated with LangChain, combining live market data (Yahoo/Polygon.io), sentiment/technical indicators, LSTM-based forecasting, and LLM-generated recommendations.”
Staff Software Engineer specializing in SaaS platforms across Healthcare and FinTech
Senior AI/ML Engineer specializing in LLM systems and FinTech platforms
Senior Full-Stack AI Engineer specializing in LLM/RAG and production ML platforms
Jayaprakash Majji
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference
“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”