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Remote Rn Triage Jobs in Bridgewater, MA (NOW HIRING)

Bcbsri

DSNP RN Care Manager

Providence, RI · On-site +1

$73K - $110K/yr

It's why we offer flexible work arrangements that include remote and hybrid opportunities and paid ... Active and unrestricted RN license issued by a state participating in the Nurse Licensure Compact ...

Sedgwick

Field Case Manager

Boston, MA · On-site +1

... remote work environment that allows face to face interaction with injured workers and medical ... RN licensure preferred; or graduate degree in health or human services field required with one of ...

York Risk Services

Field Case Manager

Boston, MA · On-site +1

... remote work environment that allows face to face interaction with injured workers and medical ... RN licensure preferred; or graduate degree in health or human services field required with one of ...

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Remote Rn Triage information

See Bridgewater, MA salary details

$12

$39

$56

How much do remote rn triage jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for remote rn triage in Bridgewater, MA is $39.26, according to ZipRecruiter salary data. Most workers in this role earn between $32.12 and $44.90 per hour, depending on experience, location, and employer.

What does a typical workday look like for a remote RN triage?

A typical workday for a Remote RN Triage nurse involves fielding calls or online messages from patients seeking medical advice, assessing symptoms based on established protocols, and determining the appropriate level of care or urgency. You may document all interactions in electronic health records, coordinate with physicians or advanced practice providers, and sometimes follow up with patients to ensure their concerns are addressed. While you work independently from a remote location, you are often part of a collaborative virtual team and may attend regular team meetings or briefings. This structure helps ensure consistent, quality patient care and provides ongoing peer support.

What is a remote RN triage?

A Remote RN Triage job involves providing telephone-based or virtual patient care, assessing symptoms, offering medical advice, and directing patients to the appropriate level of care. Triage nurses rely on clinical protocols to determine whether a patient needs emergency care, a doctor's visit, or self-care at home. They work for hospitals, clinics, insurance companies, or telehealth services. This role requires strong critical thinking, decision-making skills, and an active RN license.

What are the key skills and qualifications needed to thrive in the remote RN triage position, and why are they important?

To thrive as a Remote RN Triage nurse, you need an active registered nurse (RN) license, strong clinical judgment, and experience in patient assessment and telephone triage. Familiarity with telehealth platforms, electronic health records (EHRs), and triage protocols such as Schmitt-Thompson guidelines is typically required. Excellent listening skills, compassion, and the ability to clearly communicate medical advice over the phone or online set outstanding candidates apart. These competencies are critical to accurately evaluating patient needs, ensuring safe care from a distance, and providing reassurance in potentially urgent situations.

What are popular job titles related to Remote Rn Triage jobs in Bridgewater, MA? For Remote Rn Triage jobs in Bridgewater, MA, the most frequently searched job titles are:
What cities near Bridgewater, MA are hiring for Remote Rn Triage jobs? Cities near Bridgewater, MA with the most Remote Rn Triage job openings:
Remote Rn Triage jobs near you
Infographic showing various Remote Rn Triage job openings in Bridgewater, MA as of August 2026, with employment types broken down into 3% As Needed, 58% Full Time, 16% Part Time, and 23% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $81,667 per year, or $39.3 per hour.

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

OutcomesAI

Boston, MA • On-site, Remote

Full-time

Re-posted 3 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.