Job Description
Are you ready to architect the future of intelligent systems? Nexus Neural Systems is at the forefront of generative AI, pushing the boundaries of what is possible in large language models and autonomous reasoning. We are looking for a visionary Senior Machine Learning Engineer to join our elite R&D team in San Francisco.
You will work on mission-critical infrastructure, optimizing model performance, and deploying cutting-edge architectures that serve millions of users globally. We value clean code, intellectual curiosity, and the drive to solve the industry's most complex algorithmic challenges.
Responsibilities
- Design, train, and deploy large-scale Transformer-based models in a production environment.
- Optimize neural network architectures for latency, throughput, and energy efficiency.
- Collaborate with research scientists to translate high-level theoretical concepts into scalable code.
- Implement advanced MLOps pipelines to ensure data integrity and continuous model improvement.
- Perform rigorous code reviews and provide technical mentorship to junior engineers.
- Troubleshoot and resolve complex system bottlenecks in distributed training clusters.
- Contribute to internal patents and publish findings in top-tier AI journals.
Qualifications
- Master’s or Ph.D. in Computer Science, AI, Robotics, or a related quantitative field.
- 5+ years of professional experience in deep learning, specifically with PyTorch or JAX.
- Expert-level proficiency in Python and C++ for high-performance computing.
- Deep understanding of LLM fine-tuning, RAG architectures, and reinforcement learning.
- Demonstrated experience with distributed training (NCCL, Ray, or Megatron-LM).
- Strong track record of shipping production-grade machine learning features at scale.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.