ML Research Engineer (Computer Vision)

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 seeking Research Engineers to join our growing AI research team. You will build and scale state-of-the-art foundation models that power Metamorphic's next-generation systems. This is a high-impact, technically deep role at the frontier of ML research and engineering, with a focus on developing, scaling, and productionizing computer vision deep learning models for real-world multimodal data pipelines. A strong background in computer vision is essential. 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 the ability to move from research code to production-quality systems
• Are a pragmatic problem solver with attention to scalability and reliability
• Are comfortable operating in fast-moving, research-driven environments
• 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

$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, Electrical Engineering, Physics, or another quantitative field
• Proficiency in Python with strong software engineering practices (testing, modular design, reproducibility, version control)
• Practical experience with deep learning frameworks such as PyTorch
• Practical experience with workflow orchestrators such as Ray, Dagster, Airflow, DVC or similar and experience in implementing and maintaining complex machine learning pipelines
• Practical experience in collecting, maintaining, and working with large multimodal datasets
• Strong experience in deep learning solutions to computer vision and image processing tasks (depth estimation, object detection, segmentation, etc.)
• Hands-on experience in optimizing inference efficiency, memory usage, and throughput of computer vision models.

NICE TO HAVE

• Experience conducting long-term development and/or research projects in academia or industry
• Familiarity with large-scale data processing pipelines
• Contributions to open-source ML projects
• Publications at top-tier conferences such as CVPR, ICCV, ECCV, ICLR, ICML, NeurIPS

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.