# ML Research Engineer \(Distributed Training\) - Company: [Metamorphic]() - Location: Palo Alto - Team: Technical Staff - Employment type: Full Time - Salary: $200K – $280K - Posted: March 26, 2026 ## Job description # About Metamorphic Metamorphic is developing new approaches to intelligence by combining machine learning with large-scale experimental neuroscience, informed by the principles that make the brain efficient, flexible, and robust. We are building foundation models trained on rich, continuous neural data — a high-resolution model of the brain at a scale never before possible. Our founding team spans machine learning, neuroscience, and neurotechnology, with prior work including the [MICrONS project](https://www.nature.com/immersive/d42859-025-00001-w/index.html), [Neuropixels](http://neuropixels.org/), and the [Enigma project](https://www.enigmaproject.ai/), as well as foundational scientific contributions in learning, neural computation, and generative modeling. Our work sits at the frontier of AI research, and we believe the highest-impact discoveries will come from researchers and engineers working as a single, tightly collaborative team. The name Metamorphic reflects our belief that the next advances in intelligence will come from a change in form, beyond scale — from artificial to natural intelligence. # About the Role We are hiring Research Engineers to join our growing AI research team. You will work on building and scaling the distributed systems that enable training Metamorphic’s state-of-the-art foundation models across thousands of GPU’s. This is a high-impact, technically deep role working at the frontier of ML research and engineering. You will design and optimize our distributed training framework, implement advanced parallelism strategies, build fault-tolerant infrastructure, and provide the tooling researchers need to run large-scale experiments quickly and reproducibly. You'll have substantial autonomy to shape foundational technical decisions on a small, high-impact team. You'll thrive in this role if you: * Have significant software engineering experience and can move quickly without sacrificing rigor * Are able to balance research goals with practical engineering constraints * Are happy to take on tasks outside your job description to support the team * Enjoy pair programming and deeply collaborative work * Are eager to learn more about machine learning research in a novel scientific domain * Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research * Have ambitious goals for AI progress and are excited to create the best outcomes over the long term We offer: * The chance to work on one of the most scientifically consequential AI projects being pursued today * A small, world-class team where your contributions directly shape the science and the company * Competitive compensation and benefits, along with visa sponsorship * Strong mentorship and career development # **Salary Range** $200,000 - $280,000 USD Based on experience. We additionally offer a competitive equity package and comprehensive benefits, as well as visa sponsorship for international candidates. # **Minimum Qualifications** * Bachelor's degree or equivalent experience in Computer Science, Machine Learning, or a related field * Strong software engineering skills with a proven track record of building complex systems * Hands-on experience building and debugging distributed training infrastructure (PyTorch FSDP, DeepSpeed ZeRO, Megatron, TorchTitan, or similar) and optimizing advanced parallelism strategies * Strong understanding of GPU architecture and performance: memory hierarchy, tensor core utilization, bandwidth vs compute limitations * Strong understanding of the NVIDIA ecosystem: CUDA, NCCL, NVLink/NVSwitch topologies, mixed-precision training (MXFP8/NVFP4), and profiling tools * Deep familiarity with PyTorch internals, including torch.distributed, autograd, memory management, and torch.compile * Experience with cloud/HPC environments and job orchestration across hundreds of GPUs # **Nice to Have** * Experience building fault-tolerant training pipelines, including checkpointing, automatic recovery, and infrastructure for reproducible experimentation * Experience with the latest in mixture-of-experts architectures, diffusion model training, or multimodal models * Experience with inference serving frameworks (vLLM, TensorRT-LLM) or building custom inference solutions We encourage you to apply even if you do not believe you meet every single qualification. If you don't see a role that fits, we encourage you to submit a general application and tell us how you'd like to contribute to our mission. ## Apply [Apply on Metamorphic]() Canonical job page: