Senior Software Engineer
Builds high-performance infrastructure for brain reverse-engineering via large-scale AI models and neuroscience-informed simulations. Architects systems, optimizes RL environments, and scales research prototypes to production.
Responsibilities
- Architect high-performance infrastructure for training large-scale models and running complex simulations.
- Design and optimize custom RL environments informed by neuroscience.
- Write clean, fast, production-grade code that boosts research velocity.
- Turn research prototypes into scalable production systems.
- Tackle technical bottlenecks from low-level optimization to high-level system design.
Qualifications
- Produce clean, maintainable, well-tested code at startup pace, balancing rigor with quick iteration.
- Deep experience architecting complex systems from scratch, understanding trade-offs.
- Extreme adaptability to dive into new domains like neuroscience.
- Track record tackling difficult engineering challenges like massive scale distributed systems or low-level optimization.
Sr. Applied AI Engineer
Build and evolve shared AI/ML infrastructure including LLM proxy server, observability tooling, and ML Ops platform capabilities. Focus on LLM Ops and ML Ops to improve how models are accessed, monitored, evaluated, deployed, and governed in production.
Software Engineer, Generative AI
Build and scale secure generative AI services and applications using Python, LLMs, and modern frameworks. Own architecture decisions from proposal through production deployment for enterprise customers.
AI Engineer
As an AI Engineer, you will build and deploy AI-powered solutions to drive business outcomes across Sales, Marketing, and Customer Support. This role requires strong engineering skills, systems thinking, and a product mindset to own initiatives from discovery to deployment.