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Remote Scribe Jobs in Boston, MA (NOW HIRING)

Bond Vet

Veterinarian - Boston - Lynnfield

Boston, MA · On-site +1

$150K - $180K/yr

You'll have supportive staff both in the clinic and remotely to assist you with callbacks, scribing ... We have a highly-skilled remote team of nurses to lend support with client needs, triaging cases ...

All JobsScribe JobsRemote Scribe JobsRemote Scribe Jobs in Boston, MA

Remote Scribe information

See Boston, MA salary details

$9

$19

$26

How much do remote scribe jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for remote scribe in Boston, MA is $19.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.44 and $22.21 per hour, depending on experience, location, and employer.

What is a Remote Scribe job?

A Remote Scribe is a professional who assists healthcare providers by documenting patient encounters in real-time from a remote location. They listen to medical consultations via a secure connection and update electronic health records (EHRs) with notes, diagnoses, and treatment plans. This role helps physicians focus more on patient care by reducing their administrative workload. Remote Scribes must have strong listening skills, medical terminology knowledge, and attention to detail.

What are some common challenges faced by Remote Scribes, and how can they be overcome?

Remote Scribes often face challenges like maintaining focus during long periods of transcription and accurately capturing complex medical information while working independently. It is important to create a distraction-free workspace and use reliable technology, such as noise-cancelling headphones and up-to-date computers, to minimize errors. Additionally, proactively communicating with physicians or supervisors can clarify any ambiguities and ensure that patient records are complete and accurate. Regularly reviewing medical terminology and staying current with updates in EHR systems can also help Scribes remain proficient and effective in their roles.

What are the key skills and qualifications needed to thrive in the Remote Scribe position, and why are they important?

To thrive as a Remote Scribe, you need excellent listening skills, fast and accurate typing abilities, and a solid understanding of medical terminology, typically supported by a background in healthcare or life sciences. Familiarity with electronic health record (EHR) systems and secure communication platforms is often required, and some employers prefer candidates with certifications like Certified Medical Scribe Specialist (CMSS). Attention to detail, adaptability, and strong written communication set standout candidates apart in a remote work environment. These skills are vital for ensuring precise medical documentation, efficient workflow, and effective collaboration with healthcare providers.

What are the most commonly searched types of Scribe jobs in Boston, MA? The most popular types of Scribe jobs in Boston, MA are:
What are popular job titles related to Remote Scribe jobs in Boston, MA? For Remote Scribe jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Remote Scribe jobs in Boston, MA look for? The top searched job categories for Remote Scribe jobs in Boston, MA are:
What cities near Boston, MA are hiring for Remote Scribe jobs? Cities near Boston, MA with the most Remote Scribe job openings:
Remote Scribe jobs near you
Infographic showing various Remote Scribe job openings in Boston, MA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $41,269 per year, or $19.8 per hour.

Tech Lead -- ASR / TTS / Speech LLM (IC + Mentor)

OutcomesAI

Boston, MA • On-site, Remote

Full-time

Posted 19 days ago

Job description

OutcomesAI is a healthcare technology company building an AI-enabled nursing platform designed to augment clinical teams, automate routine workflows, and safely scale nursing capacity.
Our solution combines AI voice agents and licensed nurses to handle patient communication, symptom triage, remote monitoring, and post-acute care — reducing administrative burden and enabling clinicians to focus on direct patient care. 

Our core product suite includes: 
● Glia Voice Agents – multimodal conversational agents capable of answering patient calls, triaging symptoms using evidence-based protocols (e.g., Schmitt-Thompson), scheduling visits, and delivering education and follow-ups. 
● Glia Productivity Agents – AI copilots for nurses that automate charting, scribing, and clinical decision support by integrating directly into EHR systems such as Epic and Athena. 
● AI-Enabled Nursing Services – a hybrid care delivery model where AI and licensed nurses work together to deliver virtual triage, remote patient monitoring, and specialty patient support programs (e.g., oncology, dementia, dialysis). 

Our AI infrastructure leverages multimodal foundation models — incorporating speech recognition (ASR), natural language understanding, and text-to-speech (TTS) — fine-tuned for healthcare environments to ensure safety, empathy, and clinical accuracy. All models operate within a HIPAA-compliant and SOC 2–certified framework. OutcomesAI partners with leading health systems and virtual care organizations to deploy and validate these capabilities at scale. Our goal is to create the world’s first AI + nurse hybrid workforce, improving access, safety, and efficiency across the continuum of care.  

Lead the end-to-end technical development of speech models (ASR, TTS, Speech-LLM) — from architecture, training strategy, and evaluation to production deployment.You’ll act as an individual contributor and mentor, guiding a small team working on model training, synthetic data generation, active learning, and inference optimization for healthcare applications. As a Tech Lead specializing in ASR, TTS, and Speech LLM, you will spearhead the technical development of speech models. This involves everything from architectural design and training strategies to evaluation and production deployment.

This role is a blend of individual contribution and mentorship. You will guide a small team focused on model training, synthetic data generation, active learning, and inference optimization, all within the context of healthcare applications.
What You’ll Do
  • Own the technical roadmap for STT/TTS/Speech LLM model training: from model selection → fine-tuning → deployment.
  • Evaluate and benchmark open-source models (Parakeet, Whisper, etc.) using internal test sets for WER, latency, and entity accuracy.
  • Design and review data pipelines for synthetic and real data generation (text selection, speaker selection. voice synthesis, noise/distortion augmentation).
  • Architect and optimize training recipes (LoRA/adapters, RNN-T, multi-objective CTC + MWER).
  • Lead integration with Triton Inference Server (TensorRT/FP16) and ensure K8s autoscaling for 1000+ concurrent streams.
  • Implement Language Model biasing APIs, WFST grammars, and context biasing for domain accuracy.
  • Guide evaluation cycles, drift monitoring, and model switcher/failover strategies.
  • Mentor engineers on data curation, fine-tuning, and model serving best practices.
  • Collaborate with backend/ML-ops for production readiness, observability, and health metrics.
Desired Skills
  • Deep expertise in speech models (ASR, TTS, Speech LLM) and training frameworks (PyTorch, NeMo, ESPnet, Fairseq).
  • Proven experience with streaming RNN-T / CTC architectures, LoRA/adapters, and TensorRT optimization.
  • Telephony robustness: Codec augmentation (G.711 μ-law, Opus, packet loss/jitter), AGC/loudness norm, band-limit (300–3400 Hz), far-field/noise simulation.
  • Strong understanding of telephony noise, codecs, and real-world audio variability.
  • Experience in Speaker Diarization,  turn detection model, smart voice activity detectionEvaluation: WER/latency curves, Entity-F1 (names/DOB/meds), confidence metrics.
  • TTS : VITS/FastPitch/Glow-TTS/Grad-TTS/StyleTTS2, CosyVoice/NaturalSpeech-3 style transfer, BigVGAN/UnivNet vocoders, zero-shot cloning.
  • Speech LLM: Model development and integration with Voice agent pipeline.
  • Experience deploying models with Triton Inference Server, Kubernetes, and GPU scaling.
  • Hands-on with evaluation metrics (WER, F1 on entities, latency p50/p95).
  • Familiarity with LM biasing, WFST grammars, and context injection.
  • Strong mentorship and code-review discipline.
Qualifications
  • M.S. / Ph.D. in Computer Science, Speech Processing, or related field.
  • 7–10 years of experience in applied ML, at least 3 in speech or multimodal AI.
  • Track record of shipping production ASR/TTS models or inference systems at scale.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.