Job Description
We are pioneering the next generation of Agentic AI architectures designed to solve complex real-world problems. As we look toward the technological landscape of 2026, we are seeking a visionary Senior AI Research Engineer to lead our breakthrough initiatives in Large Language Models (LLMs) and Multimodal AI systems.
In this role, you will bridge the gap between cutting-edge research and scalable production systems, working alongside world-class engineers and data scientists to build the future of artificial intelligence.
Why Join Us?
- Work on foundational models that will define the AI industry for the next decade.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first policy with a hub in the heart of San Francisco.
Responsibilities
- Research and develop novel neural network architectures, specifically focusing on attention mechanisms and efficient transformer variants.
- Optimize large-scale model training pipelines to reduce inference latency and improve memory efficiency.
- Collaborate with the product team to translate research findings into deployable AI agents and tools.
- Implement rigorous evaluation frameworks to measure model performance, safety, and fairness.
- Stay abreast of the latest academic breakthroughs and integrate state-of-the-art techniques into our tech stack.
- Mentor junior researchers and provide technical leadership on complex architectural challenges.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related field with a focus on Machine Learning/AI.
- Minimum of 5 years of professional experience in building and deploying large-scale AI models.
- Deep expertise in PyTorch, TensorFlow, or JAX.
- Strong understanding of NLP, LLMs, or Computer Vision fundamentals.
- Experience with distributed training frameworks (Ray, Horovod) and cloud infrastructure (AWS, GCP).
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ACL).
- Excellent communication skills and ability to work effectively in cross-functional agile teams.