Machine Learning Engineer (Data)

Job Description

About Zyphra

At Zyphra, we're building Maia—a cutting-edge multimodal agent system that combines advanced research in neural network architectures, long-term memory, and reinforcement learning. Based in Palo Alto, our team brings together talent from leading AI organizations including Google DeepMind, Anthropic, StabilityAI, Qualcomm, Neuralink, Nvidia, and Apple.

Machine Learning Engineer (Data)

About this role:

You will be a core contributor to creating, collecting, and improving Zyphra’s datasets and data pipelines across a variety of modalities. Your work will intersect with almost every team at Zyphra. You will be involved with large scale dataset collection, and implementing and optimizing highly parallel data pipelines. You will work across,

Large scale data collection across a variety of modalities (text, audio, image)

Designing and working with highly efficient, parallelized data processing pipelines across modalities

Designing and running rigorous experimental ablations to demonstrate the impact of new data improvements

While deep expertise in all areas isn't required, you should be enthusiastic about learning each aspect as needed to drive our models forward. We also strongly look for velocity over position. However, having deep expertise in at least one of the above is helpful to begin contributing immediately.

Requirements:

Strong implementation and prototyping ability – can take an idea from conception to experimentation quickly

The ability to work well with others in a high-paced research setting

Can rapidly learn new fields and are excited to implement new ideas

Excellent communication and collaboration skills and can work effectively on both research and engineering implementation at scale.

Good to have:

Experience collecting, handling, and processing large datasets

Experience with parallel python programming frameworks such as Dask

Understanding of the state-of-the-art in dataset curation across modalities

A generally meticulous nature and strong interest in actually looking at data and sanity checking things

Strong grasp of proper experimental methodology for running rigorous ablations and other hypothesis testing

Understanding of and interest in large-scale highly parallel data processing pipelines.

Proficiency with Pytorch and Python.

Experience contributing to large pre-existing codebases and rapidly getting up to speed.

Previously published machine learning research in well-respected venues.

Postgraduate degree in scientific subject (Computer Science, EE/EECS, Mathematics, Physics, Machine Learning)

Culture:

Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued

We strongly value new and crazy ideas and are very willing to bet big on new ideas

We move as quickly as we can; we aim to make the bar to impact as low as possible

We all enjoy what we do and love discussing AI

Benefits and Perks:

Medical, dental, vision and FSA plans

Competitive salary, equity and 401(k)

Relocation and immigration support on a case-by-case basis

On-site meals prepared by a dedicated culinary team; Thursday Happy Hours

General requirements:

Willing to be in-person in our office in Palo Alto

US authorization to work. We will consider O1 visa sponsorship for the right candidate

Full-time