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Vetted Model Deployment Professionals
Pre-screened and vetted.
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and scalable inference
Mid-level Full-Stack Software Engineer specializing in FinTech analytics and security
Mid-level Python Backend Developer specializing in cloud-native microservices and AI/ML platforms
Senior Data Engineer specializing in cloud-native data platforms and streaming pipelines
Mid-level Applied AI Engineer specializing in LLMs, MLOps, and real-time AI systems
Mid-level AI/ML Engineer specializing in LLMs, multilingual NLP, and low-latency MLOps
Principal business value leader specializing in AI, data, and cloud transformation
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Yue Zhao
Junior Machine Learning Researcher specializing in multimodal LLMs and computer vision
“LLM/multimodal systems builder who developed DuetGen, a practical multimodal interleaved text-image generation system using a decoupled MLLM planner and video-pretrained diffusion transformer for high-quality image generation with step-wise alignment. Built a 298K-sample interleaved dataset across 8 domains/151 subtasks and deployed a GPT-5-based automated evaluation framework; also has LangChain-based multimodal agent orchestration experience with custom state management and reliability testing.”
Abhinav Bandaru
Junior Data Scientist specializing in Generative AI and agentic LLM systems
“LLM/agentic-systems builder who has shipped production tools for investment research and procurement insights, including a company screener that processes thousands of conference-listed companies using FireCrawl + Google Search + Gemini. Demonstrates strong orchestration expertise (LangGraph multi-agent graphs), performance optimization (async/batching to sub-30s), and pragmatic reliability/evaluation practices with stakeholder-friendly UX (real-time cost tracking and model/parameter toggles).”
Akshitha Singireddy
Junior Software Engineer specializing in data engineering and computer vision
“Former Amazon intern who owned an end-to-end computer vision system to detect package anomalies in fulfillment centers, from data collection/labeling to production deployment on AWS (EC2/S3) with a Streamlit live-monitoring dashboard. Also has ML-in-production experience deploying and updating a recommendation model on Kubernetes (Minikube) with CI/CD via GitHub Actions, plus prior SDE experience with Jenkins-based pipelines and on-prem to AWS migration work using Glue.”
Shashank Sathola
Mid-level Python Backend Developer specializing in cloud-native microservices and AI/ML platforms
“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”
Mid-level Full-Stack Python Developer specializing in FinTech and ML-driven automation