Deskripsi Pekerjaan
Are you ready to architect the brain behind the next generation of autonomous systems? Nexus Intelligence Labs is seeking a Senior Machine Learning Engineer to join our core research team in the heart of San Francisco's financial district. We are not just deploying models; we are building the foundational infrastructure that allows AI to reason, plan, and interact with the physical world in real-time.
In this role, you will own the full lifecycle of large-scale deep learning models—from novel architecture design and distributed training on massive GPU clusters to low-latency inference optimization for edge deployment. You will collaborate directly with Research Scientists and Robotics Engineers to bridge the gap between theoretical breakthroughs and production-grade reality.
We offer a culture of radical ownership, zero bureaucracy, and a compute budget limited only by your ambition. If you have a track record of pushing SOTA on transformer architectures, diffusion models, or reinforcement learning, and you want your code to power physical intelligence, apply now.
Tanggung Jawab
- Design, implement, and scale novel deep learning architectures (Transformers, Diffusion, LLMs) for multimodal perception and decision-making.
- Optimize distributed training pipelines (PyTorch, JAX, FSDP, DeepSpeed) across 100+ GPU clusters for maximum throughput and stability.
- Develop high-performance inference engines (TensorRT, ONNX Runtime, custom CUDA kernels) targeting sub-10ms latency on edge hardware.
- Build and maintain robust MLOps pipelines: data versioning, automated evaluation, shadow deployment, and continuous monitoring.
- Collaborate with Robotics & Simulation teams to define data strategies, simulation-to-real transfer protocols, and reward modeling.
- Conduct rigorous ablation studies and publish findings internally; contribute to top-tier conferences (NeurIPS, ICML, CVPR, ICLR) as appropriate.
- Mentor junior engineers and establish best practices for code quality, reproducibility, and experiment tracking.
Kualifikasi
- M.S. or Ph.D. in Computer Science, Machine Learning, Robotics, or equivalent practical experience (5+ years industry ML experience).
- Expert-level proficiency in Python, PyTorch/JAX, and C++ for high-performance computing contexts.
- Proven track record of training and deploying large-scale models (>1B parameters) in production environments.
- Deep understanding of GPU architecture, memory management, kernel fusion, and distributed systems (NCCL, MPI).
- Strong software engineering fundamentals: Git, CI/CD, Docker/Kubernetes, testing, and clean architecture principles.
- Experience with multimodal data (vision, language, proprioception) and sim2real transfer techniques.
- Publications in top-tier ML venues or significant open-source contributions to major ML frameworks.