Job Description
Join the Pioneers of the 2026 Era
Year 2026 AI is at the forefront of defining the future of artificial intelligence. We are seeking a visionary Senior Generative AI Engineer to lead the development of next-generation Large Language Models (LLMs) and autonomous agents. You will be instrumental in shaping the technological landscape of 2026, optimizing model performance, and deploying scalable AI solutions that redefine human-computer interaction. If you are passionate about pushing the boundaries of what is possible in AI, we want to meet you.
Why Join Us?
- Work on cutting-edge projects with a mission to accelerate the arrival of AGI.
- Competitive equity package and top-tier compensation.
- Collaborative, inclusive, and innovative work culture in the heart of San Francisco.
Responsibilities
- Model Architecture & Development: Design and implement state-of-the-art Generative AI models, focusing on LLMs, transformers, and diffusion models.
- Optimization & Inference: Engineer high-performance inference pipelines to reduce latency and cost while maximizing output quality for real-time applications.
- Research & Innovation: Conduct research on novel techniques in prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) to stay ahead of industry trends.
- Deployment: Manage the end-to-end deployment of AI models to cloud infrastructure (AWS/GCP) and edge devices, ensuring robustness and security.
- Collaboration: Partner with cross-functional teams of data scientists, product managers, and engineers to translate technical requirements into scalable solutions.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field.
- Experience: 5+ years of professional experience in software engineering or machine learning, with a strong focus on Deep Learning and NLP.
- Technical Skills: Proficiency in Python, PyTorch or TensorFlow; extensive experience with Hugging Face Transformers and LangChain.
- Model Tuning: Demonstrated experience in training, fine-tuning, and optimizing large-scale language models.
- System Design: Strong understanding of distributed systems, cloud architecture, and MLOps best practices.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.