jobctl

Machine Learning Engineer - Recommendation Systems

SpaceXSI - Palo Alto, CA - original posting ->
Status
Open
Remote policy
Not stated
Employment type
Not stated
Salary
Not stated
Categories
Engineering
Tech
clickhousekafkasparkml
Source
xai
First observed
2026-08-18 21:02 UTC
Last seen
2026-10-13 05:08 UTC
Source claims posted
2025-04-11 03:21 UTC
Consecutive misses
0 of 3

What the posting says

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to understand the universe and help expand humanity’s knowledge and capabilities. We work across the full Super Intelligence stack: compute (Colossus supercomputers), models (Grok), and applications (Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X). We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

ABOUT THE ROLE:

We’re seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with a engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You’ll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences.

RESPONSIBILITIES:

Designing and architecting recommendation algorithms across various product surfaces

Leverage all of SpaceXSI's infra and AI stacks to dramatically enhance the user experience

Write data pipelines and training jobs that continuously learn from product data.

Iterate and improve the algorithm by gathering user feedback in real time through experimentation

Ensuring scalability and efficiency of machine learning systems

BASIC QUALIFICATIONS:

Knowledge of data infrastructure like Kafka, Clickhouse, and Spark

Experienced in implementing recommender systems and/or deep learning applications at industrial scale

Skilled in one or more DL software frameworks such as JAX or PyTorch

Exceptional candidates may be experienced in writing CUDA kernels

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Quality

Completeness: 45%
Honesty: 100%

Based on 18 observation(s).

Timeline

  1. *
    #161921 2026-08-18 21:02 UTC
    Published
  2. ~
    #167647 2026-08-19 01:02 UTC
    Modified
    • source_updated_at
      2026-08-18T15:14:36-04:00->2026-08-18T18:10:46-04:00
  3. ~
    #199871 2026-08-20 01:16 UTC
    Modified
    • source_updated_at
      2026-08-18T18:10:46-04:00->2026-08-19T18:53:03-04:00
  4. ~
    #227176 2026-08-21 00:25 UTC
    Modified
    • Title
      Member of Technical Staff - Recommendation Systems->Machine Learning Engineer - Recommendation Systems
    • source_updated_at
      2026-08-19T18:53:03-04:00->2026-08-20T19:05:52-04:00
  5. ~
    #231316 2026-08-21 04:27 UTC
    Modified
    • source_updated_at
      2026-08-20T19:05:52-04:00->2026-08-20T20:36:54-04:00
  6. ~
    #259278 2026-08-21 23:53 UTC
    Modified
    • source_updated_at
      2026-08-20T20:36:54-04:00->2026-08-21T18:24:01-04:00
  7. ~
    #388588 2026-08-26 22:37 UTC
    Modified
    • source_updated_at
      2026-08-21T18:24:01-04:00->2026-08-26T17:48:54-04:00
  8. ~
    #394216 2026-08-27 06:39 UTC
    Modified
    • source_updated_at
      2026-08-26T17:48:54-04:00->2026-08-26T23:12:24-04:00
  9. ~
    #407461 2026-08-27 22:40 UTC
    Modified
    • source_updated_at
      2026-08-26T23:12:24-04:00->2026-08-27T18:09:48-04:00
  10. ~
    #557795 2026-09-03 21:32 UTC
    Modified
    • Locations
      Palo Alto, California->Palo Alto, CA
    • source_updated_at
      2026-08-27T18:09:48-04:00->2026-09-03T14:58:20-04:00
  11. ~
    #564549 2026-09-04 05:32 UTC
    Modified
    • source_updated_at
      2026-09-03T14:58:20-04:00->2026-09-04T00:53:32-04:00
  12. ~
    #646362 2026-09-08 23:51 UTC
    Modified
    • source_updated_at
      2026-09-04T00:53:32-04:00->2026-09-08T18:33:02-04:00
  13. ~
    #963276 2026-09-24 06:03 UTC
    Modified
    • source_updated_at
      2026-09-08T18:33:02-04:00->2026-09-23T23:22:06-04:00
  14. ~
    #975021 2026-09-24 18:07 UTC
    Modified
    • source_updated_at
      2026-09-23T23:22:06-04:00->2026-09-24T13:08:26-04:00
  15. ~
    #1100304 2026-09-30 22:44 UTC
    Modified
    • source_updated_at
      2026-09-24T13:08:26-04:00->2026-09-30T16:41:12-04:00
  16. ~
    #1295359 2026-10-12 13:22 UTC
    Modified
    • Description
      SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our...->SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where...
  17. ~
    #1311432 2026-10-13 01:08 UTC
    Modified
    • Description
      SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where...->SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where...
    • source_updated_at
      2026-09-30T16:41:12-04:00->2026-10-12T19:35:19-04:00
  18. ~
    #1314406 2026-10-13 05:08 UTC
    Modified
    • Organisation
      SpaceXAI->SpaceXSI