We are seeking a Research Engineer to join our AI research team, working on building and scaling state-of-the-art large language models. The ideal candidate will have significant software engineering experience and a deep understanding of large language models. The role involves designing data annotation and evaluation pipelines, running large-scale experiments, and building tooling to accelerate research.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
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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 โ 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, Neuropixels, and the Enigma project, 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 โ from artificial to natural intelligence.
About The Role
We are seeking Research Engineers to join our growing AI research team. You will work on building and scaling state-of-the-art large language models that power Metamorphicโs next generation of foundation models. This is a high-impact, technically deep role working at the frontier of ML research and engineering. In this role you will interact with many parts of the research and engineering stack, from model architecture and pretraining to evaluation, tooling, and infrastructure. you will design data annotation and evaluation pipelines, run large-scale experiments, and build tooling that accelerates research in service of pushing the quality and scale of our language and multimodal models. 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
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- 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
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$175,000 - $250,000 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 or equivalent experience
- Strong software engineering skills with a proven track record of building complex systems
- Deep understanding of large language models and/or multimodal models: pretraining, fine-tuning, RLHF/alignment, post-training, and evaluation
- Proficiency in Python and modern deep learning frameworks (PyTorch preferred)
- Experience training and scaling foundation models, particularly in the context of language modeling
- Experience designing and managing large-scale data annotation or data processing pipelines
- Track record of building evaluation and benchmarking frameworks for language or multimodal models
- Experience developing internal tooling, libraries, or abstractions that improve research velocity
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- Familiarity with distributed training frameworks (DeepSpeed, TorchTitan, Megatron, or similar)
- Experience with multimodal or VLA models
- Familiarity with large-scale data processing
- Contributions to open-source ML projects or libraries
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