We have a set system for compensation as part of being transparent.

You can use formula below to see what your compensation might look like when you’re joining TabbyML, and to see how it might develop over time.

$$ TotalSalary = Role \times Location \times Level \times Step + Equity $$

• Role
  • $185,000 Software Engineer
  • $225,000 Machine Learning Engineer
• Location
  • United States
    • 1.0 San Francisco, California
    • 0.9 Seattle, Washington
    • Texas
      • 0.8 Dallas / Austin
      • 0.75 Houston
      • 0.74 San Antonio
      • 0.65 Everywhere else
    • 0.7 Hawaii
    • Massachusetts
      • 0.85 Boston
      • 0.74 Everywhere else
  • German
    • 0.65 Munich/Nuremberg
    • 0.65 Frankfurt/Stuttgart
    • 0.65 Hamburg/Bremen
    • 0.65 Berlin/Leipzig
    • 0.6 Everywhere else
  • China
    • 0.6 All
  • United Kingdom
    • 0.67 London, England
    • 0.6 Everywhere else, England
• Level
  • 0.59 Junior
  • 0.78 Intermediate
  • 1 Senior
  • 1.2 Staff
• Step
  • 0.85 - 0.94 Learning
  • 0.95 - 1.04 Established
  • 1.05 - 1.1 Thriving
  • 1.11 - 1.2 Expert

Level

More experience does not correlate with increased importance. Seniority is not a title - we don't believe in having a huge hierarchy of roles, as everyone needs to feel like the owner of the company that they are.

We pay more experienced team members a greater amount since it is reasonable to expect this correlates with an increase in skill - being able to ship faster through less time having to work things out for the first time is valuable. Experienced hires can help upskill the less experienced hires on the team too. Team members who have less experience can see a steady increase in pay over time as they increase their experience and skill.

We believe at first increased skill comes from more time spent in the role. Over time, this judgement becomes more subjective and is instead based on the speed with which you can ship or help the team to ship, the quality of your prioritization and decision-making, as well as your technical approach.

Step

Within each level, we believe there's a place to have incremental steps to allow for more flexibility. We define these as follows:

• Learning: Starting to match expectations.
• Established: Matching expectations.
• Thriving: Exceeding expectations.
• Expert: Exceeding expectations consistently.

With exception of team members at the very beginning of their career, we hire into the Established step by default. This will give everyone the opportunity to be set up for success and leave enough room for salary increases, without the need to move up in seniority.