Job Description
Are you ready to shape the future? Horizon 2026 Labs is pioneering the next generation of autonomous systems. We are looking for a visionary Senior AI Engineer to lead our flagship Project 2026, an initiative dedicated to redefining human-computer interaction through advanced generative AI.
In this role, you won't just write code; you will architect the brain of our next-generation platform. You will work in a fast-paced, high-performance environment where innovation is the only metric that matters. We offer a competitive compensation package, equity packages, and the opportunity to work with world-class researchers.
Why Join Us?
- Impactful Work: Directly influence the trajectory of AI development in 2026 and beyond.
- Top-Tier Team: Collaborate with industry veterans from Google DeepMind, OpenAI, and Tesla.
- Flexible Work: Hybrid model supporting remote and in-office collaboration in the heart of SF.
Responsibilities
- Design, develop, and deploy state-of-the-art Large Language Models (LLMs) and multimodal systems tailored for enterprise applications.
- Optimize existing deep learning models for production environments, focusing on latency, throughput, and memory efficiency.
- Collaborate with cross-functional teams (Product, Design, and Engineering) to translate complex business requirements into technical specifications.
- Conduct rigorous research and experimentation to explore new frontiers in generative AI and reinforcement learning.
- Mentor and guide junior data scientists and ML engineers, fostering a culture of continuous learning and technical excellence.
- Ensure code quality, scalability, and security standards are met across all AI infrastructure.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Strong understanding of LLM architectures, fine-tuning techniques (PEFT, LoRA), and RAG (Retrieval-Augmented Generation).
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of shipping production-grade AI products to market.
- Excellent problem-solving skills and the ability to thrive in ambiguous, fast-moving environments.