Job Description

Build AI to co-invent the future

We’re a team of passionate technologists building AI agents that help people design and make new products, services, and discoveries.

We offer you the opportunity to solve challenging and meaningful problems, build useful and seamless products, and help move the world forward.

Team

We’re passionate technologists and builders. Our team has published award-winning AI research, includes alumni from Caltech, and Professors from Caltech and UT Austin.
We're backed by top-tier investors and partners: Eric Schmidt, Caltech, Jeff Dean, and JP Millon.

Values

We strive for excellence, focus, and impact.
We value thinking from first principles, learning fast, and getting things done.
We want to empower you to take ownership in fulfilling our mission.
Above all, we value team spirit, sharing the ups and downs, and achieving great things together.

What you'll do

You’ll be a key team member that will help set the course, take ownership, and execute rapidly.

You will design, train, and evaluate hybrid AI systems that perform well at scale and make optimal trade-offs.
Apply Occam’s Razor by defining and applying simple design principles.
Solve min-max problems: how can we do more with less?
Accelerate our work by removing operational and tooling bottlenecks.

What we look for

You want to solve challenging and meaningful real-world problems.
You have a track record in a technical domain, e.g., machine learning, computer science, physics, math.
You have developed and implemented machine learning algorithms, models, and tools.
You have strong programming and math abilities.
You have clear verbal and written communication skills
You have strong conceptual and structured thinking.
You are willing and able to learn quickly.
You have team spirit.
You can independently structure, plan, prioritize, and get things done.
You have a drive for excellence, a sense of urgency, and bias to action.

It would be nice to have

Open-source projects, published research papers, or other examples of experience in using machine learning.
Experience with applying deep learning, reinforcement learning, unsupervised learning, and other techniques to large-scale problems.
Experience with distributed computing and handling large datasets.

Our compensation, benefits, and perks

Competitive salary
Stock options
100% covered premium health, dental, and vision insurance.
Wellness benefits (e.g., gym, fitness classes, physical therapy).
Retirement 401k: 100% match of your 401k deferrals up to 4% of your compensation.
Commuter benefits
Daily meals in the office
Training and development budget, e.g., for domestic conferences.
Flexible working hours
Unlimited PTO (with manager approval)
Team-building events and celebrations

The target salary range for this position is $150,000 - $250,000 annually. Actual offers and compensation are based on individual experience, performance, and other considerations, and might lie outside this range.

Process

Step 1: CS fundamentals assessment

To prepare for this, it would be good to have a solid understanding of basic data structures (e.g., lists, hash maps, stacks, queues, trees) and algorithms (e.g., sorting, depth-first vs breadth-first search, dynamic programming).

Step 2: Interviews

Optional: presentation on previous (research) projects.
2x machine learning interviews: 1:1 interviews where we will go over a machine learning problem in a collaborative code editor. The goal is to assess your current knowledge level of machine learning, relevant math/statistics concepts, coding, and general problem solving and communication skills.
1x CS / technical communication interview. A mix of coding and debugging/analyzing existing code.
1x discussion of behavioral cases and your career goals.

Step 3: Offer