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Vetted LoRA Professionals
Pre-screened and vetted.
Sai supriya
Mid-level AI/ML Engineer specializing in LLM alignment, safety, and scalable inference
“Built and productionized an AWS-hosted, Kubernetes-orchestrated RAG assistant that enables natural-language Q&A over internal document repositories with grounded answers and citations. Demonstrates strong applied LLM engineering: hallucination mitigation, hybrid retrieval + re-ranking, and rigorous evaluation via benchmarks and A/B testing, plus real-world scaling of compute-heavy inference with dynamic batching and monitoring.”
Krishna Reddy
Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants
“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Principal Full-Stack Software Engineer specializing in IoT/IIoT platforms
Mid-level AI/ML Engineer specializing in GPU-accelerated LLM and vision systems
Senior AI/ML Engineer specializing in personalization, recommendations, and forecasting
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and GPU-accelerated cloud systems
Mid-level Computer Vision Engineer specializing in robotics perception and mapping
Junior AI Software Engineer specializing in LLM systems and retrieval (RAG)
Mid-level AI/ML Engineer specializing in LLMs, ranking systems, and MLOps
Mid-level AI Solutions Architect & Product Leader specializing in enterprise GenAI systems
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Dhruv Arora
Senior Generative AI Implementation Consultant specializing in RAG and agentic AI on cloud
“LLM/RAG practitioner who built an AWS-based enterprise document search and summarization platform with RBAC and scaled it to 10K+ users, solving relevance issues via contextual chunking and hybrid retrieval. Also designed agentic workflows for a telecom forecast-validation use case using sub-agents, tool APIs, and strict context management, and has proven pre-sales influence (supported a $300K manufacturing deal with a roadmap-driven pitch).”
Chenghui Cai
Director of Applied Sciences specializing in reinforcement learning and agentic AI for finance
“Embodied AI/robotics ML engineer with hands-on experience deploying POMDP-based reinforcement learning controllers on real mobile robots and vehicle fleets. Strong in sim-to-real robustness (domain randomization) and production rollout practices (HIL, shadow-mode, canaries, safety instrumentation), and has published related work (mentions a NeurIPS paper).”
Keerthana Senthilnathan
Junior Machine Learning Engineer specializing in LLM systems and inference reliability
“ML/LLM infrastructure-focused engineer who built a production stateful LLM inference service that cuts latency and GPU compute for repeated/overlapping prompts via caching with correctness guardrails. Strong in Kubernetes-based deployment and reliability engineering, using A/B testing and similarity-based evaluation to quantify performance gains without sacrificing output quality.”
Senior Applied Scientist specializing in LLMs, GenAI, and agentic systems
Director of Engineering specializing in capital markets risk, trading systems, and AI/ML platforms
Mid-level Machine Learning Engineer specializing in real-time fraud detection and edge AI
Staff Machine Learning Engineer specializing in LLMs, recommendations, and MLOps
Mid-level AI/ML Engineer specializing in GenAI agents and production ML systems
Mid-level AI/ML Engineer specializing in LLM, RAG, and multimodal systems