Job Description
Shape the Future of Technology at Nebula Dynamics
We are seeking a visionary Senior AI Engineer to join our elite team in San Francisco. As we project towards a 2025 landscape dominated by advanced generative models and autonomous systems, you will be at the forefront of building the next generation of intelligent solutions. If you are passionate about pushing the boundaries of machine learning and want to define the standard for AI in the coming years, we want to hear from you.
Why Join Us?
- Work with state-of-the-art hardware (NVIDIA H100 clusters) and cutting-edge frameworks.
- Competitive compensation package with equity options.
- Flexible remote-first policy with a premium office in the heart of SF.
At Nebula Dynamics, we don't just predict the future; we engineer it.
Responsibilities
- Architect & Deploy: Design and implement scalable machine learning infrastructure for large-scale generative AI applications.
- Model Optimization: Fine-tune large language models (LLMs) and transformer architectures to maximize inference speed and accuracy on edge devices.
- R&D Leadership: Conduct research on novel neural network architectures and integration strategies for 2025 tech stacks.
- Collaboration: Partner with cross-functional teams of data scientists, engineers, and product managers to translate complex AI concepts into user-centric products.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- System Reliability: Ensure high availability and fault tolerance of AI inference pipelines in production environments.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- Experience: 5+ years of professional experience in software engineering, with at least 3 years dedicated to machine learning or AI research.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with Hugging Face Transformers or LangChain.
- Cloud Expertise: Deep understanding of cloud infrastructure (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
- Mathematical Fluency: Strong grasp of linear algebra, calculus, probability, and statistics.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.