Job Description
Join the Architects of Tomorrow. Nebula Horizon Systems is a pioneer in predictive intelligence, tasked with defining the technological landscape of 2026 and beyond. We are seeking a visionary Senior AI Research Engineer to lead our core research initiatives, focusing on Large Language Models, generative AI, and autonomous decision-making systems.
In this pivotal role, you will not just write code; you will shape the roadmap that our clients will rely on in the coming years. You will work in a high-performance environment where cutting-edge research meets scalable production engineering.
Why Join Us?
- Work on projects that define the industry standards for 2026.
- Competitive equity package and top-tier salary.
- State-of-the-art hardware and research facilities in the heart of SF.
Responsibilities
- Research Leadership: Drive the technical vision for our 2026 AI roadmap, conducting original research in NLP, Computer Vision, and Reinforcement Learning.
- Model Development: Design, train, and fine-tune proprietary Large Language Models to achieve state-of-the-art performance benchmarks.
- Prototype Engineering: Translate theoretical research into production-ready APIs and microservices, ensuring high availability and low latency.
- Collaboration: Partner with cross-functional teams including product managers, data scientists, and backend engineers to integrate AI solutions into client-facing products.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Performance Optimization: Continuously optimize model inference speed and accuracy to handle massive data streams in real-time.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a strong portfolio of published research or deployed models.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX; deep understanding of neural network architectures.
- Problem Solving: Exceptional ability to solve complex, unstructured problems and navigate ambiguity in a fast-paced startup environment.
- Communication: Excellent verbal and written communication skills, capable of presenting complex technical concepts to non-technical stakeholders.
- Tools: Experience with cloud platforms (AWS/GCP/Azure), containerization (Docker/Kubernetes), and MLOps pipelines.