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Machine Learning Engineer, Voice

Speak · San Francisco · Hybrid · Active · Ashby

Job facts

FieldValue
CompanySpeak
TitleMachine Learning Engineer, Voice
Normalized title-
Department / teamEngineering / Engineering, Machine Learning
LocationSan Francisco, 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 Speak.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 San Francisco.Open
Department jobsActive postings in Engineering.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

CompanySpeak
Source24ca8f88-a6d8-465b-84d9-5a17e80a0a5d
ATS providerAshby

Description

About us Our mission is to reinvent the way people learn, starting with language. Learning a language can change a life by opening doors to new cultures, careers, and communities. Two billion people around the world are actively trying to learn a language, but the best way to learn (one-on-one tutoring) is hard to access at scale and hasn’t been meaningfully improved in decades. Speak is building a human-level, AI-powered tutor in your pocket: a conversation-first experience that lets learners actually speak, get instant feedback, and progress through carefully designed lessons. The result is a complete path from beginner to confident speaker across multiple languages. Speak first launched in South Korea in 2019, where Speak has now become the number one language learning app, and we now serve learners across many markets and 15+ languages. Speak is one of the world’s leading AI companies, with over $150m raised in venture investment from OpenAI, Accel, Founders Fund, Khosla Ventures, and more, with a distributed team across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana. About this role We are looking for an experienced Machine Learning Engineer to join our team and help develop cutting-edge speech recognition models that help teach language fluency. In this role you will take ownership of the end-to-end modeling pipeline, from training and experimentation to deployment and monitoring. You will also work closely with Product teams to design innovative learning experiences and measure the efficacy of production models as they affect our end users. We are a small, dynamic team where you will contribute as a developer and thought partner on team projects like ASR, assessment, pronunciation, content personalization, and much more. This is an incredibly exciting time to join an ML team designing a personalized learning experience that will revolutionize language learning for millions of learners worldwide — come join us! What you'll be doing Training and deploying ASR models end-to-end, including monitoring, performance tracking, and retraining Improving the pronunciation model that provides precise feedback, and make it more central to our learning app Creating metrics to measure ASR performance across tasks and languages Expanding our ASR systems to new languages and markets Building and maintaining data infrastructure such as training/evaluation datasets and labeling pipelines What we're looking for Extensive experience training large models on GPUs and deploying custom deep learning models Proficiency in Python and common Deep Learning frameworks like PyTorch Demonstrated experience owning ML pipelines end to end, from POC to production Strong communication skills and the ability to explain complex ML concepts to non-technical stakeholders Sharp product sense and an ability to think broadly and cross-functionally about model quality in the context of user experience Bonus Experience with speech or audio Office San Francisco, CA Why work at Speak Join a fantastic, tight-knit team at the right time:  we're growing very quickly, we've most recently raised our Series C from some of the top investors in the valley, and we've achieved product-market fit in our initial markets. You'd join at a magical time when a single person could significantly change the course of the company. Do your life's work with people you’ll love working with:  we care strongly about our craft and want every person at Speak to feel like they're growing every day. We believe in the idea that working with people you both enjoy and have respect for makes everything better. We hire thoughtfully and only work with people we admire deeply. Global in nature:  We're live in over 40 countries and launching in a number of new markets soon. We have dedicated offices in San Francisco, Ljubljana, Seoul, and Tokyo, and you’ll have the opportunity to talk to users in each of these regions on a regular basis as well as travel. Impact people's lives in a major way:  Learning a language is one of the single most life-changing skills one can learn, and right now 99% of people never achieve their goal because the process is broken. We’re helping millions of people achieve their goals and improve their lives. Speak does not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Full job record

Job IDd2e24b99ad19e81dd0b6035fd089fcf84564a7a1
Org IDea6fe4dc-e761-4563-afdd-b2140adc8761
Source ID24ca8f88-a6d8-465b-84d9-5a17e80a0a5d
Board ID24ca8f88-a6d8-465b-84d9-5a17e80a0a5d
Providerashby
Provider Job Keye78edff4-5135-4c68-932d-e449ee460ea3
TitleMachine Learning Engineer, Voice
Normalized Title
Statusactive
Activeyes
Location TextSan Francisco
DepartmentEngineering
TeamEngineering, Machine Learning
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CitySan Francisco
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://jobs.ashbyhq.com/speak/e78edff4-5135-4c68-932d-e449ee460ea3
Apply URLhttps://jobs.ashbyhq.com/speak/e78edff4-5135-4c68-932d-e449ee460ea3/application
First Seen At2026-05-29 05:24:07Z
Last Seen At2026-06-06 19:39:55Z
Last Checked At2026-06-06 19:39:55Z
Last Changed At2026-05-29 05:24:07Z
Inactive At
Source Posted At
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=speak/date=2026-06-06/2026-06-06T19-39-51-654Z-308dc55c442f6888a1f44995043af5fed0e2f8eb7bdb67e5c75d7f22ba06d2f2.json
Event Fields
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  "last_changed_at": "2026-05-29T05:24:07.454Z",
  "active_status": "active"
}
Parsed Structured
{
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  "location": {
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    "city": "San Francisco",
    "region": "CA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.75
  },
  "salary_max": null,
  "salary_min": null,
  "inferred_at": "2026-06-06T19:39:55.600Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "San Francisco",
      "city": "San Francisco",
      "region": "CA",
      "country": "United States",
      "is_remote": false,
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    "countries": [
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    ]
  },
  "remote_policy": "hybrid",
  "salary_period": null,
  "workplace_type": "hybrid",
  "salary_currency": null
}
Extensions
{}
Native Structured
{
  "id": "e78edff4-5135-4c68-932d-e449ee460ea3",
  "team": "Engineering, Machine Learning",
  "title": "Machine Learning Engineer, Voice",
  "jobUrl": "https://jobs.ashbyhq.com/speak/e78edff4-5135-4c68-932d-e449ee460ea3",
  "address": null,
  "applyUrl": "https://jobs.ashbyhq.com/speak/e78edff4-5135-4c68-932d-e449ee460ea3/application",
  "isListed": true,
  "isRemote": false,
  "location": "San Francisco",
  "updatedAt": null,
  "apiVersion": "ashby-non-user-graphql-v1",
  "department": "Engineering",
  "publishedAt": null,
  "workplaceType": "Hybrid",
  "employmentType": "FullTime",
  "secondaryLocations": []
}
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