Founding Member of Technical Staff

    • Asari AI
  • Pasadena, CA
  • Posted 5 days ago | Updated 3 hours ago

Overview

On Site
$150,000 - $250,000
Full Time

Skills

Expect
FOCUS
IMPACT
UPS
Artificial intelligence
Data processing
Design
Razor
Computer science
Physics
Open source
Deep learning
Unsupervised learning
Distributed computing
Insurance
Training and development
Budget
Team building
Data structure
Algorithms
Presentations
Research
Machine Learning (ML)
Mathematics
Statistics
Problem solving
Communication
Technical communication
Software development
Debugging

Job Details

Job Description

Job Description
Build AI to co-invent the future

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

We get energized by solving challenging and meaningful problems, building useful and seamless products, and helping move the world forward.

Our team has published award-winning AI research. We're fortunate to be backed by top-tier investors and partners: Eric Schmidt (former CEO of Google and former Executive Chairman of Alphabet), Caltech, Jeff Dean (Chief Scientist, Google DeepMind and Google Research), and JP Millon.

Values
  • We expect excellence, focus, and impact.

  • We think from first principles, learn fast, and get things done.

  • We empower you to take ownership in fulfilling our mission.

  • Above all, we value team spirit, sharing the ups and downs, achieving great things together, and having fun while doing so.

What you'll do
  • Be a key team member that will help set the course, take ownership, and execute rapidly.

  • Design, train, and evaluate hybrid AI systems that perform well at scale and make optimal trade-offs.

  • Build data processing pipelines

  • Implement machine learning models

  • Run machine learning workloads at scale using distributed computing

  • Define and apply simple design principles that scale (Occam's Razor)

  • 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 enjoy and are energized by solving 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

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

  • Background and reference checks.

Compensation Range: $150K - $250K

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