Job Description
We are on a mission to redefine the boundaries of artificial intelligence. Nexus AI Labs is seeking a visionary Senior AI Engineer to join our elite team in San Francisco. If you are passionate about building scalable, large-scale language models and have a deep understanding of deep learning architectures, we want to meet you.
As a Senior AI Engineer at Nexus, you won't just write code; you will architect the intelligence that powers the next generation of enterprise applications. You will work directly with our CTO and lead a team of brilliant minds to solve complex problems in natural language processing, computer vision, and reinforcement learning.
Why Join Us?
- Work with state-of-the-art hardware and cloud infrastructure.
- Competitive equity package and top-tier health benefits.
- Flexible remote-first culture with a hub in the heart of SF.
Responsibilities
- Model Architecture: Design, implement, and optimize deep neural network architectures for large-scale generative AI models.
- Research & Development: Stay at the forefront of AI research, implementing novel techniques such as Transformers, Diffusion Models, and RLHF.
- Performance Engineering: Reduce inference latency and optimize model resource consumption for edge deployment.
- Mentorship: Lead technical mentorship for junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Collaboration: Partner with cross-functional teams including product managers, designers, and backend engineers to integrate AI capabilities seamlessly.
- Productionization: Ensure robustness and scalability of AI models in high-traffic production environments.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of professional experience in machine learning engineering, with a focus on large language models (LLMs) or deep learning.
- Tools: Proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Knowledge: Strong understanding of statistical learning theory, neural network theory, and optimization algorithms.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver creative engineering solutions.