.png){kind=logo}
Vetted LoRA Professionals
Pre-screened and vetted.
Mid-level ML Engineer specializing in MLOps, data engineering, and GenAI/RAG systems
Mid-level Robotics Engineer specializing in vision-language-action models and sim-to-real deployment
Mid-level Software Engineer specializing in AI/GenAI and cloud-native backend systems
Mid-level AI Engineer specializing in NLP, computer vision, and MLOps
Junior Generative AI Engineer specializing in LLM fine-tuning and RAG pipelines
Mid-level AI Engineer specializing in NLP, LLM fine-tuning, and RAG systems
Junior AI/ML Engineer specializing in RAG, multi-agent systems, and enterprise NLP
Mid-level Backend & AI Engineer specializing in agentic systems and scalable microservices
Mid-level Generative AI & Computer Vision Research Engineer specializing in diffusion and multimodal models
Junior Machine Learning Engineer specializing in LLM agents, knowledge graphs, and multimodal AI
Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP
sathwik kuchana
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG on AWS
“Built and deployed an LLM-powered clinical decision support and risk monitoring platform for mental health at Valuai.io, emphasizing low-latency, evidence-grounded responses and crisis-safe behavior with clinician escalation. Strong production agent-orchestration background (LangChain/CrewAI) plus rigorous evaluation (clinician-in-the-loop + evaluator agent) and large-scale synthetic testing; also applied multi-agent workflows to document verification and fraud detection during an AI internship at Nixacom.”
Sree Sai Preetham Nandamuri
Mid-level Data Scientist specializing in Generative AI and LLMOps
“Built a production-grade, semi-automated document recognition and classification system for large volumes of scanned PDFs, starting from little/no labeled data and handling highly variable scan quality. Deployed on AWS using SageMaker + Docker and orchestrated on EKS with a microservices design that scales CPU-heavy OCR separately from GPU inference, with strong reliability controls (validation, fallbacks, retries, readiness probes).”
VenkataRamireddy Gaddam
Junior IoT/Embedded Systems Engineer specializing in ROS 2, LoRa, and sensor fusion
“Robotics/embedded developer with hands-on ROS 2 and micro-ROS experience on ESP32, building a remote-controlled high-power LED system. Worked across power distribution (buck-boost constant 30V), sensor calibration with real-time data checks, and long-range WiFi connectivity using an omnidirectional antenna achieving 100m+ coverage.”
Vamsi Mandhapati
Mid-level Full-Stack Java Engineer specializing in Generative AI and cloud microservices
“Full-stack engineer who has delivered production customer analytics/dashboard features using Next.js App Router + TypeScript on the frontend and Java Spring Boot microservices on the backend. Demonstrates strong production ownership (monitoring latency/error rates/adoption) plus hands-on performance work across React rendering and Postgres query/index optimization, and has implemented Temporal-like durable workflows with retries and idempotency.”
Venkatalakshmi Kottapalli
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
“LLM engineer/data analyst who built a production RAG QA assistant over the Jurafsky & Martin NLP textbook to reduce hallucinations and provide explainable, source-grounded answers. Experienced with LangChain/LangGraph orchestration, retrieval optimization (embeddings, vector DBs, caching), and rigorous evaluation/monitoring (Retrieval@K, A/B tests, telemetry/drift). Previously communicated analytics insights to non-technical stakeholders at GS Analytics using Power BI and simplified reporting.”
Sree Manasa Vuppu
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG
“Internship at Discovery Education building a production LLM/RAG chatbot that let marketing and sales teams query and interpret Looker/BI dashboards in natural language, with responses grounded in compliance and state education standards. Emphasizes rigorous evaluation (faithfulness/precision/recall/latency) plus user-feedback analytics, and used LangChain for orchestration, chunking/context-window control, and integration with enterprise sources like SharePoint.”
Vedasahaja bandi
Mid-level AI Engineer specializing in NLP, computer vision, and healthcare analytics
“Data scientist who has built production LLM agents (GPT-4o + LangChain + RAG) to automate analyst-style ad hoc CSV analysis with guardrails and GPT-as-a-judge evaluation. Also delivered an explainable healthcare NLP system for ICD code classification by collaborating closely with clinicians, using a hybrid rule-based decision tree + BERT model to reach 97% accuracy and cut manual review time.”