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Vetted Reinforcement Learning Professionals
Pre-screened and vetted.
Ilija Hadzic
Principal Robotics & Autonomy Research Engineer specializing in localization and multi-robot navigation
“Highly experienced robotics software engineer building ROS/ROS2 systems for fleets of autonomous mobile robots (Clearpath Jackal/Husky and custom platforms), spanning localization, navigation, and multi-robot coordination. Has published work at ICRA (including RL-based local planning and heterogeneous robot coordination via a ROS-to-ZMQ bridge) and maintains open-source ROS modules, with strong simulation, debugging, and CI/CD practices.”
Jack Ahn
Executive Technology & R&D Leader specializing in Generative AI and Digital Health
“Hands-on engineering leader currently at Vianai (GenAI enterprise applications) building AI-assisted data exploration/insights products with Python and React. Previously Corporate VP of Digital Health at Samsung Electronics, where they helped close key partner deals by demonstrating API-driven openness and led a major Samsung Health modernization from monolith to microservices for horizontal scalability and faster, safer iteration.”
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Entry-Level Software Engineer specializing in AI developer platforms
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Staff Data Scientist specializing in machine learning, deep learning, and big data
Junior Software Engineer specializing in AI/ML and recommendation systems
Executive AI/ML Engineer specializing in LLMs, NLP, and production ML systems
Senior Software Engineer specializing in full-stack systems and ML-driven platforms
Jesse Olson
Executive AI technology leader specializing in agentic AI and enterprise transformation
“Candidate is exploring a startup in the autonomous agentic AI space and is approaching it with a disciplined founder mindset. They are evaluating market opportunity, competition, customer pain, ROI, technical feasibility, and MVP options while already speaking with potential customers across verticals to validate needs and buying processes.”
Christopher Sipola
Senior Machine Learning Engineer specializing in LLMs and recommendation systems
“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”
Pradeep Nadella
Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling
“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Executive AI researcher and founder specializing in generative and embodied AI
Senior AI Full Stack Engineer specializing in generative AI and ML systems
Senior AI/ML Engineer specializing in recommender systems, GenAI, and applied ML
Senior Machine Learning Engineer specializing in on-device AI and large-scale deep learning systems
Senior AI/ML Engineering Manager specializing in NLP, computer vision, and MLOps
Junior Machine Learning Engineer specializing in fraud detection and healthcare ML