Job Description
Shape the future of Generative AI at Nexus Neural Systems.
We are looking for a visionary AI Engineer to join our core research and development team in San Francisco. You will be at the forefront of deploying large-scale transformer models, optimizing inference pipelines, and creating production-grade solutions that impact millions of users globally.
At Nexus, we value intellectual curiosity, rigorous engineering standards, and a passion for solving complex, non-linear problems. If you thrive at the intersection of deep learning research and scalable infrastructure, we want to meet you.
Responsibilities
- Design and train state-of-the-art Large Language Models (LLMs) and diffusion models.
- Optimize neural network architectures for low-latency inference in production environments.
- Collaborate with cross-functional teams to integrate generative AI features into our core product suite.
- Implement advanced fine-tuning techniques, including RLHF and PEFT, on proprietary datasets.
- Maintain high code quality standards through rigorous peer reviews and automated testing.
- Stay current with emerging research in AI and contribute to our internal technical whitepapers.
- Mentor junior engineers and foster a culture of engineering excellence.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related quantitative field.
- 3+ years of professional experience in deep learning, specifically with PyTorch or JAX.
- Expertise in Transformer architectures, attention mechanisms, and model quantization.
- Proficiency in Python and C++ for high-performance computing.
- Proven track record of deploying machine learning models into high-traffic cloud production environments (AWS/GCP/Azure).
- Familiarity with distributed training frameworks such as DeepSpeed, Megatron, or Ray.
- Strong background in data structures, algorithms, and system design.