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HomeCompaniesEmbedding VcAI Trainer: Code Generation

AI Trainer: Code Generation

Embedding Vc · Palo Alto, CA · Hybrid · Active · Ashby

Job facts

FieldValue
CompanyEmbedding Vc
TitleAI Trainer: Code Generation
Normalized title-
Department / teamEmbedding Labs / Embedding Labs
LocationPalo Alto, CA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary-
Statusactive
ATS providerAshby
Posted / first seen / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Embedding Vc.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Ashby.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Palo Alto.Open
Department jobsActive postings in Embedding Labs.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyEmbedding Vc
Source1778ba28-5545-4943-8b05-a24cc4b8d57e
ATS providerAshby

Description

AI Trainer: Code Generation Overview We are building a focused group of engineers to improve how large language models reason through real world code. This initiative centers on evaluating and refining multi step reasoning trajectories derived from real GitHub repositories, with the goal of producing higher quality, more reliable code generation outputs. This is a long term project requiring strong engineering judgment rather than surface level labeling. Contributors will work directly with complex code paths and reasoning flows across multiple platforms. What You Will Do You will analyze and refine multi step code reasoning trajectories generated from real production repositories. This includes: Reviewing model generated reasoning sequences Identifying logical inconsistencies or weak reasoning steps Improving trajectory structure to produce stronger, production grade outputs Evaluating reasoning quality across different programming environments The work is closer to debugging model logic and reasoning systems than to traditional annotation tasks. What We Are Looking For We are looking for engineers with strong hands on development experience and deep familiarity with real codebases. You should: Be proficient in at least two mainstream programming languages such as Python, C++, Java, TypeScript, or JavaScript Have real world development experience in areas such as backend systems, frontend applications, algorithms, testing, or infrastructure Be comfortable reading and reasoning through large GitHub repositories Have strong written communication skills Experience contributing to high visibility or high star GitHub repositories is a strong plus. Additional Details We expect to onboard approximately 10 to 20 engineers for this long term initiative. A short qualification exercise may be required prior to joining.

Full job record

Job IDfc7cec9c0871cb505aab78590e2650e6ec6fe9df
Org IDc5a8bcb7-1823-4346-bc28-58a31aa0108c
Source ID1778ba28-5545-4943-8b05-a24cc4b8d57e
Board ID1778ba28-5545-4943-8b05-a24cc4b8d57e
Providerashby
Provider Job Key5b38ad5c-ea98-46af-92e9-b4e01f746c41
TitleAI Trainer: Code Generation
Normalized Title
Statusactive
Activeyes
Location TextPalo Alto, CA
DepartmentEmbedding Labs
TeamEmbedding Labs
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CityPalo Alto
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://jobs.ashbyhq.com/embedding-vc/5b38ad5c-ea98-46af-92e9-b4e01f746c41
Apply URLhttps://jobs.ashbyhq.com/embedding-vc/5b38ad5c-ea98-46af-92e9-b4e01f746c41/application
First Seen At2026-05-29 05:13:54Z
Last Seen At2026-06-06 19:27:19Z
Last Checked At2026-06-06 19:27:19Z
Last Changed At2026-05-29 05:13:54Z
Inactive At
Source Posted At
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=embedding-vc/date=2026-06-06/2026-06-06T19-27-14-918Z-cb2fbbab5adba6bf3c76e88eb57b2d7bc8158922f14c23669ef70fe0c6b0d8a6.json
Event Fields
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Parsed Structured
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Extensions
{}
Native Structured
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  "department": "Embedding Labs",
  "publishedAt": null,
  "workplaceType": "Hybrid",
  "employmentType": "FullTime",
  "secondaryLocations": []
}
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