LinkedIn MLE vs Harvey MLE offer eval — stability or startup upside?

Two recent Bay Area senior AI/ML offers had a pretty interesting tradeoff.

One is from LinkedIn, with lower headline TC but more predictable public-company compensation. The other is from Harvey, with higher first-year TC and a much larger equity grant, but the RSU value is based on the company’s private valuation.

LinkedIn — Sr. MLE, Bay Area

• Base: $240K
• Signing bonus: $40K
• RSU: $560K over 4 years
  • Vesting: 25 / 25 / 25 / 25
  • First-year equity: $140K
• Annual bonus: $24K
• First-year total: $444K

Harvey — Sr. MLE, Bay Area

• Base: $250K
• Signing bonus: $25K
• RSU: $1M over 4 years
  • Vesting: 25 / 25 / 25 / 25
  • First-year equity: $250K
• First-year total: $525K
• Additional note: Harvey RSU numbers are based on the current valuation of Harvey as of June 2026.

On paper, Harvey also looks meaningfully stronger over four years because the equity grant is almost 2x LinkedIn’s. But the quality of the comp is very different.

LinkedIn’s package is easier to value. The base, bonus, and RSUs are more straightforward, and the company is a known quantity. Harvey has more upside and probably more direct exposure to applied AI / legal AI work, but the equity depends much more on private-company valuation, liquidity timing, and how much confidence someone has in the company’s growth.

Discussion

• Would Harvey’s higher upside and AI-native role outweigh the private-company equity risk?
• Or would LinkedIn’s stability, public-company comp, and more predictable career path make it the better risk-adjusted choice?