Research Engineer – Training

• Design, train, and iterate on state-of-the-art AI models
• Scale training pipelines, datasets, and distributed workflows

We’re inviting an experienced, generalist AI research engineer to join our core team at Mother, building our first computer, the Mother I. We are looking for a self-starter who is a highly motivated and autonomous operator to join us at our Mountain View office.

What is Mother?

We are tool builders. Our mission is to create tools that enable endless creativity and amplify our inherent human abilities.

What is Mother I?

Too much of today’s AI compute is concentrated in the hands of a few large companies. We believe in local and open-source AI—your AI should truly be your own.

Mother I is an AI supercomputer designed to run a wide range of open-source models locally. At its core is a software stack that makes it remarkably easy to run models and perform powerful tasks—directly on your own machine.

What you’ll do

• Design, train, and iterate on state-of-the-art AI models
• Build and scale systems for efficient, large-scale model training
• Experiment rapidly with architectures, datasets, and training techniques to improve model performance
• Optimize training workflows through distributed training, data pipelines, and hardware utilization
• Work across the stack—from model design and loss functions to training infrastructure and tooling
• Collaborate with product and inference teams to bring research models into production

What you bring

• 4+ years of experience in machine learning engineering, applied research, or systems engineering
• Strong experience with deep learning frameworks (e.g., PyTorch)
• Solid understanding of training dynamics, optimization, and evaluation of ML models
• Experience building or working with training pipelines and large datasets
• Strong CS fundamentals, including performance, memory, and compute efficiency
• Ability to move from idea → experiment → validated result quickly
• Comfort working on ambitious, open-ended problems

Nice to have

• Experience with distributed training (e.g., DDP, FSDP, DeepSpeed)
• Familiarity with data curation, augmentation, and dataset scaling strategies
• Experience training large models (LLMs, multimodal, or similar)
• Exposure to training optimization techniques (mixed precision, gradient checkpointing, etc.)
• Interest in emerging model architectures and research directions

Tech stack

Python · PyTorch · CUDA (nice to have) · Rust (nice to have) · PostgreSQL · Linux (Ubuntu/Debian)

Perks

• Computer setup of your choice (plus a Mother I Computer)
• Blue Shield Platinum PPO plans with $0 paycheck deduction (covers all dependents)
• Dental (including orthodontic coverage) and vision plans with $0 paycheck deduction
• Company paid life insurance
• Fully stocked kitchen and catered lunch 5 days a week
• Office in Mountain View (near Caltrain) with free, easy parking Unlimited PTO

How to apply

Send us an email with a copy of your resume or LinkedIn, your GitHub, and any projects you think we should see to [email protected]