Define and drive the research roadmap for core AI capabilities spanning LLMs, ASR/speech understanding, retrieval-augmented generation, and agentic systems.
Design, train, fine-tune, and evaluate state-of-the-art models, taking them from prototype to robust, production-grade systems.
Lead the architecture of scalable training and inference pipelines that operate reliably on real customer-scale data.
Establish rigorous evaluation frameworks, benchmarks, and quality bars for model performance, safety, and reliability.
Partner closely with product, platform, and ML engineering teams to ship research into customer-facing features.
Mentor senior and mid-level engineers, set technical standards, and act as a force multiplier across the AI org.
Stay ahead of the field, evaluate emerging techniques, and represent Level AI's technical work externally where appropriate.

Degree in Computer Science, Machine Learning, or a related field, or equivalent research experience; typically 6+ years applying ML/AI in production settings.
Deep expertise in modern deep learning, with strong command of LLMs, transformers, and at least one of speech/ASR, NLP, information retrieval, or multimodal modeling.
A track record of taking research from idea to deployed, scaled product—not just publications, but shipped impact.
Expert-level proficiency in Python and a major deep learning framework (PyTorch preferred), with strong software engineering fundamentals.
Hands-on experience training and serving large models, including distributed training, optimization, and efficient inference.
Demonstrated technical leadership: setting direction, mentoring engineers, and influencing across teams.
Clear communicator able to convey complex technical ideas to both research and product audiences.

Principal AI Research Engineer

Key skills