{"schemaVersion":"jobsearcher.job.v1","id":"a602f897450bb203fa144a5f","url":"https://jobsearcher.com/jobs/a602f897450bb203fa144a5f","canonicalUrl":"https://jobsearcher.com/jobs/a602f897450bb203fa144a5f","title":"ML Engineer: Speech & LLMs","description":"About KnowtexKnowtex is building the future of voice AI operating systems for clinicians, transforming how healthcare documentation happens at the point of care. We are experiencing rapid growth across both commercial health systems and federal healthcare, with our ambient documentation platform scaling to thousands of clinicians across hundreds of specialties.We are at an inflection point where advances in speech, language models, and clinical AI can fundamentally change how clinicians interact with technology, giving them more time to focus on what matters most: their patients.Position OverviewWe are hiring two ML Engineers / Researchers to help build the next generation of Knowtex's AI stack.We are looking for researchers with deep expertise in one of two areas:Speech & Audio: Build state-of-the-art medical speech-to-text systems using our large proprietary dataset of real-world clinical audio, with the goal of bringing more of our speech stack in-house. Large Language Models: Develop and optimize models for clinical documentation and structured clinical reasoning, improving quality, cost, latency, and control. You do not need to be an expert in both areas. We are looking for exceptional depth in either speech/audio modeling or LLMs.These are research-heavy roles with a direct path to production. You will design experiments, build datasets and evaluation systems, train and fine-tune models, and work closely with engineering and clinical teams to deploy successful approaches at scale.This role plays a central part in defining Knowtex's long-term ML strategy.Key ResponsibilitiesSpeech & AudioDevelop and train speech recognition models optimized for medical conversations across hundreds of specialtiesLeverage Knowtex's large proprietary clinical audio dataset to train and fine-tune domain-specific speech modelsResearch approaches for improving medical terminology recognition, speaker attribution, punctuation, timestamps, and robustness across accents and clinical environmentsBuild rigorous speech evaluation frameworks beyond traditional WER, including medical terminology and clinically significant error measurementExplore modern speech architectures, self-supervised learning, speech foundation models, and audio-language modelsOptimize models for low-latency, real-time inference at production scaleLarge Language ModelsDevelop and optimize models for generating high-quality clinical documentation, including SOAP notes and specialty-specific note formatsBuild models for downstream clinical tasks such as medication extraction, orders, ICD-10 coding, E&M coding, patient visit summaries, and other structured clinical artifactsEvaluate open-weight and proprietary model architectures and determine where fine-tuning, distillation, structured generation, or task-specific models can outperform general-purpose API-based approachesFine-tune and post-train models using Knowtex's proprietary clinical datasetsDevelop rigorous evaluation frameworks for clinical accuracy, hallucinations, completeness, formatting, and clinician preferencesResearch approaches for reducing inference cost and latency while maintaining or improving clinical qualityAcross Both TracksMove quickly from idea → dataset → experiment → evaluation → productionDesign experiments that clearly measure whether an approach improves real-world clinical outcomesBuild datasets, benchmarks, and evaluation infrastructure that make model improvements measurable and reproducibleCollaborate closely with clinicians, applied ML engineers, and platform engineersTake successful research beyond prototypes and help deploy models into productionBalance model quality with latency, inference cost, reliability, and scalabilityRequired Qualifications2+ years of experience in machine learning research or ML engineering, with deep expertise in speech/audio modeling or large language modelsStrong expertise in Python and PyTorchDeep understanding of modern transformer architectures and model training techniquesExperience training, fine-tuning, or post-training large neural modelsStrong experimental methodology and ability to independently design and execute research projectsExperience working with large-scale datasets and distributed training environmentsAbility to translate research results into production systemsStrong understanding of model evaluation and benchmarkingBachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent research experiencePreferred QualificationsFor Speech ResearchersDeep experience with automatic speech recognition (ASR)Experience training or fine-tuning Whisper, Conformer, wav2vec, or similar speech architecturesExperience with large-scale audio datasets and speech data pipelinesFamiliarity with speaker diarization, voice activity detection, streaming ASR, or audio-language modelsExperience optimizing speech models for real-time inferenceFor LLM ResearchersExperience fine-tuning or post-training open-weight LLMsExperience with supervised fine-tuning, distillation, preference optimization, or reinforcement learningExperience building LLM evaluation systems and model benchmarksExperience serving and optimizing open-weight models at scaleExperience with structured generation, tool use, or agentic systemsFor Either TrackExperience in healthcare AI, clinical NLP, or medical speechFamiliarity with clinical documentation workflows and medical terminologyKnowledge of coding systems such as ICD-10, CPT, E&M, or SNOMEDPublications at leading ML, NLP, or speech conferencesExperience deploying ML systems in HIPAA-compliant or regulated environmentsExperience working in fast-moving startup environments where researchers own projects from experimentation through productionTechnical EnvironmentAWSPython, PyTorchTransformer-based LLM and speech architecturesOpen-weight and frontier language modelsLarge-scale clinical audio and text datasetsDistributed model training and inferenceGPU-based model serving and optimizationReal-time speech and clinical AI pipelinesStructured clinical evaluation and benchmarking infrastructureCompensation & BenefitsCompetitive salaryMeaningful equity compensationUnlimited PTOPremium health, dental, and vision coverage401(k) planWork model: Hybrid In-person","company":"Knowtex","rawCompany":"knowtex","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-19T12:52:53.083Z","occupations":[{"code":"29-1127.00","title":"Speech-Language Pathologists","slug":"speech-language-pathologists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541930","title":"Translation and Interpretation Services","slug":"translation-and-interpretation-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"},{"code":"621340","title":"Offices of Physical, Occupational and Speech Therapists, and Audiologists","slug":"offices-of-physical-occupational-and-speech-therapists-and-audiologists"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"ML Engineer: Speech & LLMs","description":"About KnowtexKnowtex is building the future of voice AI operating systems for clinicians, transforming how healthcare documentation happens at the point of care. We are experiencing rapid growth across both commercial health systems and federal healthcare, with our ambient documentation platform scaling to thousands of clinicians across hundreds of specialties.We are at an inflection point where advances in speech, language models, and clinical AI can fundamentally change how clinicians interact with technology, giving them more time to focus on what matters most: their patients.Position OverviewWe are hiring two ML Engineers / Researchers to help build the next generation of Knowtex's AI stack.We are looking for researchers with deep expertise in one of two areas:Speech & Audio: Build state-of-the-art medical speech-to-text systems using our large proprietary dataset of real-world clinical audio, with the goal of bringing more of our speech stack in-house. Large Language Models: Develop and optimize models for clinical documentation and structured clinical reasoning, improving quality, cost, latency, and control. You do not need to be an expert in both areas. We are looking for exceptional depth in either speech/audio modeling or LLMs.These are research-heavy roles with a direct path to production. You will design experiments, build datasets and evaluation systems, train and fine-tune models, and work closely with engineering and clinical teams to deploy successful approaches at scale.This role plays a central part in defining Knowtex's long-term ML strategy.Key ResponsibilitiesSpeech & AudioDevelop and train speech recognition models optimized for medical conversations across hundreds of specialtiesLeverage Knowtex's large proprietary clinical audio dataset to train and fine-tune domain-specific speech modelsResearch approaches for improving medical terminology recognition, speaker attribution, punctuation, timestamps, and robustness across accents and clinical environmentsBuild rigorous speech evaluation frameworks beyond traditional WER, including medical terminology and clinically significant error measurementExplore modern speech architectures, self-supervised learning, speech foundation models, and audio-language modelsOptimize models for low-latency, real-time inference at production scaleLarge Language ModelsDevelop and optimize models for generating high-quality clinical documentation, including SOAP notes and specialty-specific note formatsBuild models for downstream clinical tasks such as medication extraction, orders, ICD-10 coding, E&M coding, patient visit summaries, and other structured clinical artifactsEvaluate open-weight and proprietary model architectures and determine where fine-tuning, distillation, structured generation, or task-specific models can outperform general-purpose API-based approachesFine-tune and post-train models using Knowtex's proprietary clinical datasetsDevelop rigorous evaluation frameworks for clinical accuracy, hallucinations, completeness, formatting, and clinician preferencesResearch approaches for reducing inference cost and latency while maintaining or improving clinical qualityAcross Both TracksMove quickly from idea → dataset → experiment → evaluation → productionDesign experiments that clearly measure whether an approach improves real-world clinical outcomesBuild datasets, benchmarks, and evaluation infrastructure that make model improvements measurable and reproducibleCollaborate closely with clinicians, applied ML engineers, and platform engineersTake successful research beyond prototypes and help deploy models into productionBalance model quality with latency, inference cost, reliability, and scalabilityRequired Qualifications2+ years of experience in machine learning research or ML engineering, with deep expertise in speech/audio modeling or large language modelsStrong expertise in Python and PyTorchDeep understanding of modern transformer architectures and model training techniquesExperience training, fine-tuning, or post-training large neural modelsStrong experimental methodology and ability to independently design and execute research projectsExperience working with large-scale datasets and distributed training environmentsAbility to translate research results into production systemsStrong understanding of model evaluation and benchmarkingBachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent research experiencePreferred QualificationsFor Speech ResearchersDeep experience with automatic speech recognition (ASR)Experience training or fine-tuning Whisper, Conformer, wav2vec, or similar speech architecturesExperience with large-scale audio datasets and speech data pipelinesFamiliarity with speaker diarization, voice activity detection, streaming ASR, or audio-language modelsExperience optimizing speech models for real-time inferenceFor LLM ResearchersExperience fine-tuning or post-training open-weight LLMsExperience with supervised fine-tuning, distillation, preference optimization, or reinforcement learningExperience building LLM evaluation systems and model benchmarksExperience serving and optimizing open-weight models at scaleExperience with structured generation, tool use, or agentic systemsFor Either TrackExperience in healthcare AI, clinical NLP, or medical speechFamiliarity with clinical documentation workflows and medical terminologyKnowledge of coding systems such as ICD-10, CPT, E&M, or SNOMEDPublications at leading ML, NLP, or speech conferencesExperience deploying ML systems in HIPAA-compliant or regulated environmentsExperience working in fast-moving startup environments where researchers own projects from experimentation through productionTechnical EnvironmentAWSPython, PyTorchTransformer-based LLM and speech architecturesOpen-weight and frontier language modelsLarge-scale clinical audio and text datasetsDistributed model training and inferenceGPU-based model serving and optimizationReal-time speech and clinical AI pipelinesStructured clinical evaluation and benchmarking infrastructureCompensation & BenefitsCompetitive salaryMeaningful equity compensationUnlimited PTOPremium health, dental, and vision coverage401(k) planWork model: Hybrid In-person","datePosted":"2026-08-19T12:52:53.083Z","dateModified":"2026-08-19T12:52:53.083Z","hiringOrganization":{"@type":"Organization","name":"Knowtex","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"a602f897450bb203fa144a5f"},"url":"https://jobsearcher.com/jobs/a602f897450bb203fa144a5f"}}