Machine learning engineer jobs at visa sponsors in Cambridge

12 employers with H-1B or green card filings at the US Department of Labor in the last 24 months have 108 open machine learning engineer roles in Cambridge right now.

Registers matched to employers 9 Oct 2026Every role re-checked on the employer's own board
open machine learning engineer roles
108
sponsors hiring
12

Sponsors with the most open machine learning engineer roles in Cambridge

CompanyOpen rolesH-1B filings, 12 monthsGreen card filingsMedian H-1B wage
Capital One69991947 for this role30$147k
Walden Robotics831 for this role—$308k
GE Vernova7448 for this role—$131k
Flagship Pioneering6101 for this role2$151k
S&P Global54412 for this role1$147k
Cambridge Mobile Telematics3159 for this role6$144k
Novartis381 for this role2$147k
Nabla Bio322 for this role—$183k
Bristol Myers Squibb1—26$133k
Toyota Research Institute12112 for this role—$217k
Cambridge Boston Alignment Initiative12—$93k
Iterative Health111 for this role1$158k

See every job at a visa sponsor

The Visa sponsor filter works across all jobs in the UK, the US, Canada and the Netherlands.

Questions

Does a sponsor licence mean this role is sponsored?

The filings show that the employer has sponsored before, not that it will sponsor this role. Ask the employer before you apply.

What do the H-1B and green card numbers mean?

They count the Labor Condition Applications (the first step of an H-1B) and the PERM labor certifications (the first step of an employment green card) the employer filed in the last 12 and 24 months, from the US Department of Labor disclosure data.

How fresh is this?

Each register is reloaded when its publisher updates it (the US and UK files weekly, Canada every quarter), and every role is re-checked on the employer's own careers board at least every 48 hours. A role that closes leaves the page at the next nightly rebuild.

Source: US Department of Labor H-1B (LCA) and green card (PERM) filings of the last 24 months × employer careers boardsUpdated 9 Oct 2026MethodologyJSONCC BY-SA 4.0