Founding AI Research Engineer

Founding AI Engineer – Core Models & Training

We’re building a deep AI lab from the ground up and looking for a Founding AI Engineer to join a small, top-tier founding team.

This is not an “apply-an-API” role.

You’ll be working at the core of the stack — training domain-specific foundation models and LLMs, pushing scale, performance, and architecture from day one.

If you care about how models are actually trained, optimized, and deployed at scale — this is the role.

• End-to-end training of Deep Learning models and LLMs
• Owning the full lifecycle: training, evaluation, fine-tuning, and post-training
• Heavy hands-on work with PyTorch / TensorFlow
• Designing scalable training pipelines and production-ready systems
• Solving performance and scale challenges in large model training
• Working closely with infra, data, and engineering to build robust AI systems
• Shaping the AI architecture, tooling, and strategy as a founding team member

• Proven, hands-on experience training LLMs
• Strong foundations in Deep Learning & Machine Learning
• Solid engineering mindset and production experience
• Experience working with cloud environments (AWS / GCP)
• Familiarity with Docker, Kubernetes, and modern ML infrastructure
• Deep experience in at least one of the following:
• Large-scale training optimization
• (e.g. parallelization, DeepSpeed, Megatron, FSDP)
• Low-level performance work
• (C++ / CUDA / Triton)
• Distributed systems for training or serving large models

• Background in cybersecurity
• Experience in early-stage startups combined with top-tier tech companies
• Alumni of elite technological military units

• Engineers who work on AI fundamentals, not just applications
• People who want to be part of a founding technical team
• Builders who want real ownership, deep technical impact, and hard problems
• Those excited by training models that don’t yet exist — and making them work at scale