Training ecosystem jobs

Pay within range listed + Bonus + Benefits + Equity

Design, implement, train, adapt, and evaluate reasoning and cognition models for unmanned autonomous platforms.
Make and validate tradeoffs among foundation-model approaches, including vision-language models (VLMs) and vision-language-action models (VLAs), specialized deep-learning models, and traditional AI/ML methods.
Develop capabilities for interpreting context, reasoning over time, coordinating among agents, and adapting to incomplete or changing information.
Build reproducible training and adaptation workflows using appropriate combinations of self-supervised learning, supervised fine-tuning, imitation learning, reinforcement learning, and distillation.
Define data requirements, training objectives, benchmarks, and evaluation methods that support meaningful comparisons among model approaches.

BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
Nice to have: MS or PhD in Computer Science, Electrical Engineering, or similar degree
Nice to have: Optimising and deploying ML models to resource-constrained hardware platforms
Nice to have: Simulation-to-real on autonomous systems
Nice to have: Unmanned autonomous systems in defense applications

Staff Engineer, Hivemind Reasoning