Machine Learning Engineer, Model Evaluations (Speech LLM) - San Francisco

About Plaud Inc. Plaud is building the world's most trusted AI work companion for professionals to elevate productivity and performance through note-taking solutions, loved by over 1,500,000 users worldwide since 2023. With a mission to amplify human intelligence, Plaud is building the next-generation intelligence infrastructure and interfaces to capture, extract, and utilize what you say, hear, see, and think.   Plaud Inc. is a Delaware-incorporated, San Francisco-based company pushing the boundary of human–AI intelligence through a hardware–software combination. With SOC 2, HIPAA, GDPR, ISO27001, ISO27701, and EN18031 compliance, Plaud is committed to the highest standards of data security and privacy protection. To learn more about Plaud, please visit https://www.Plaud.ai and follow along on Instagram , X , Facebook , LinkedIn , and YouTube   Why You Should Join Us Plaud is building the next generation intelligence infrastructure and interfaces to capture, extract, and utilize intelligence from what people say, hear, see, and think. Plaud is a bootstrapped, skyrocketing, profitable company with a $250M revenue run rate achieved in just three years. Define the next-gen paradigm for human-AI interaction. Gain exposure to cutting-edge AI for Pro tools and play a direct role in our global expansion. Work with passionate teammates who value innovation, collaboration, and customer success. Grow your career in a culture that champions continuous learning and fast career development. Market-competitive compensation, global exposure, and a vibrant, creativity-fueled work atmosphere.   You may be a good fit if you: Have a passion for turning ambiguous, subjective concepts like a voice's naturalness, expressiveness, or conversational cadence into clear, defensible, and automated metrics that researchers and leadership can rely on. Possess strong software engineering skills (especially in Python) and have experience building reliable distributed systems, data pipelines, or evaluation harnesses that can run at scale against live model checkpoints. Can deeply partner with ML researchers to define exactly what "good" looks like for a Speech LLM, translating capabilities (like ASR robustness in noisy environments or TTS emotional steerability) into measurable benchmarks. Are comfortable building and owning dashboards that track model health during training, improving signal-to-noise ratios, reducing evaluation latency, and making performance regressions impossible to miss. Rapidly debug anomalous mid-training results to determine if a drop in performance stems from the model architecture, corrupted data, or infrastructure. Communicate complex statistical results and model behaviors clearly to both technical and non-technical stakeholders.   Strong candidates may also have experience with: Speech Metrics: Deep familiarity with both traditional (WER, CER, PESQ, etc) and modern audio evaluation frameworks (automated MOS scoring). LLM-as-a-Judge: Using frontier models or finetune multi-modal LLMs to evaluate the conversational logic, transcription accuracy, audio quality, and reasoning of audio models. Human Evaluation: Managing large-scale crowdsourcing operations or preference data collection to support RLHF/DPO efforts. Observability: A strong background in statistics and experimental design, paired with experience building trusted tracking dashboards (e.g., Weights & Biases, MLflow). Adversarial Datasets: Curating complex datasets to test edge cases, such as heavy accents, overlapping speech, or highly noisy acoustic environments.   What We Offer Founding Team Initiative: Opportunity to be an early, foundational member of our core SpeechLLM lab, with meaningful ownership and impact on a fast-growing startup. Competitive Compensation: $200K - $365K base salary + performance bonus + Equity. Comprehensive Benefits: Top-tier healthcare for employees and dependents, including dental and vision, and a generous employer subsidy. Retirement Planning: 401(k) plan for full-time employees with company matching. Paid Time Off: Unlimited PTO, plus 13 paid holidays. New Parent Leave: 12 weeks of paid time off to spend time with your new family, regardless of gender. Hybrid Office: Minimum of 3x in-office per week to foster highly collaborative, fast-paced research. Gear & Perks: Choice of top-of-the-line laptops/workstations, annual offsites, and a fully stocked office.   Plaud is and will continue to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristics.

{
  "content_hash": "3a9d85c39c54d5d56fde3b85619e3d3b7aa127bb72217127b578b516ea4dc70e",
  "source_hash": "1f73288c9e9336f866161b3d51bf8d51d3e755b24def1aa9232414883f01746e",
  "last_changed_at": "2026-05-29T05:39:15.345Z",
  "active_status": "active"
}

{
  "language": "en",
  "location": {
    "raw": "San Francisco, CA",
    "city": "San Francisco",
    "region": "CA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.9
  },
  "salary_max": 365000,
  "salary_min": 200000,
  "inferred_at": "2026-06-06T20:21:54.564Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "San Francisco, CA",
      "city": "San Francisco",
      "region": "CA",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.9
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
}

{}

{
  "id": "4b0b818e-7ad1-42ef-ba0f-03901856f91f",
  "team": "Global Product R&D Center, AI R&D",
  "title": "Machine Learning Engineer, Model Evaluations (Speech LLM) - San Francisco",
  "jobUrl": "https://jobs.ashbyhq.com/Plaud/4b0b818e-7ad1-42ef-ba0f-03901856f91f",
  "address": null,
  "applyUrl": "https://jobs.ashbyhq.com/Plaud/4b0b818e-7ad1-42ef-ba0f-03901856f91f/application",
  "isListed": true,
  "isRemote": false,
  "location": "San Francisco, CA",
  "updatedAt": null,
  "apiVersion": "ashby-non-user-graphql-v1",
  "department": "Global Product R&D Center",
  "publishedAt": null,
  "workplaceType": "Hybrid",
  "employmentType": "FullTime",
  "secondaryLocations": []
}