.png){kind=logo}
Vetted Deep Learning Professionals
Pre-screened and vetted.
Senior AI/ML Engineer specializing in LLMs, NLP, and production ML systems
Mid-level Machine Learning Engineer specializing in MLOps, RAG, and real-time personalization
Director of AI/ML specializing in edge AI, computer vision, and foundation models
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and real-time recommendation systems
Mid-level Machine Learning Engineer specializing in reinforcement learning and multimodal AI
Junior AI Prompt Engineer specializing in LLMs, RAG, and conversational AI
Senior Full-Stack Engineer specializing in cloud-native SaaS and AI/ML integration
Mid-Level Software Engineer specializing in cloud platforms, ML/GenAI, and distributed systems
Mid-level AI/ML Engineer specializing in multimodal and LLM (RAG) systems
Senior AI/ML Engineer specializing in Generative AI and LLM applications
Senior Data Scientist specializing in AI/Deep Learning and applied machine learning
Mid-level AI/ML Engineer specializing in LLM RAG pipelines and cloud MLOps
Mid-level AI/ML Engineer specializing in GenAI agents and production ML systems
Mid-level Data Scientist/ML Engineer specializing in LLMs, NLP, and recommender systems
Mid-level Machine Learning Engineer specializing in Bayesian inference and reinforcement learning
Senior Software Engineer specializing in distributed systems, ML infrastructure, and search
Mid-level Agentic AI & ML Engineer specializing in LLM agents and RAG systems
Mid-level Data Scientist specializing in GenAI, LLMs, and MLOps
Saikrishna Swaminathan
Entry-level Aerospace/ADCS Researcher specializing in spacecraft controls and simulation
“Robotics/control-focused candidate with hands-on ROS2 + Gazebo experience implementing MPC with online state identification on a Crazyflie drone, including camera-based position determination fixes. Also worked on multi-agent spacecraft formation control and constellation optimization, debugging numerical drift and redesigning leader-follower control laws to handle delayed/outdated updates; uses Docker to ensure reproducible simulation results across machines.”