---
title: 'Senior Engineer — ASR / TTS / Speech LLM (Training + Eval + Integration) at OutcomesAI'
canonical: 'https://feeny.ai/job/senior-engineer-asr-tts-speech-llm-training-eval-integration-outcomesai-z390n9dzj9jz'
type: 'job'
last_seen: '2026-09-11'
---

# Senior Engineer — ASR / TTS / Speech LLM (Training + Eval + Integration) at OutcomesAI

- **Company:** OutcomesAI
- **Location:** Bengaluru, India
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-11-07
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.lever.co/outcomesai/d49c7567-6826-48bd-ab6b-ce382af53cf6

## 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.

Contribute to training, evaluation, and integration of speech models into OutcomesAI’s voice intelligence stack.You’ll work closely with the Tech Lead to develop datasets, fine-tune models, and benchmark performance across domains (RPM, Triage).

## What You’ll Do

- Prepare and maintain synthetic and real training [datasets.STT/TTS/Speech](http://datasets.STT/TTS/Speech) LLM model training: from model selection → fine-tuning → [deployment.Build](http://deployment.Build) evaluation for clinical applications (RPM, Triage, inbound/outbound).
- Build scripts for data selection, augmentation (noise, codec, jitter), and corpus curation.
- Fine-tune models using CTC/RNN-T or adapter-based recipes on multi-GPU systems.
- Implement evaluation pipelines to measure WER, entity F1, and latency; automate MLflow logging.
- Experiment with bias-aware training and context list conditioning.
- Collaborate with backend and DevOps teams to integrate trained models into inference stacks.
- Support creation of context biasing APIs and LM rescoring paths.
- Assist in maintaining benchmarks versus commercial baselines (Deepgram, Whisper, etc.).

Desired Skills

- Strong programming in Python (PyTorch, Hugging Face, NeMo, ESPnet).
- Practical experience in audio data processing, augmentation, and ASR [fine-tuning.Training](http://fine-tuning.Training): SpecAugment , speed perturb, noise/RIRs, codec+PLC+jitter sims for PSTN/[WebRTC.Streaming](http://WebRTC.Streaming) ASR: Transducer/zipformer with chunked attention, frame-sync beam search, endpointing (VAD-EOU) [tuning.Context](http://tuning.Context) biasing: WFST boosts + neural re-scoring; patient/name dictionaries; session-aware bias refresh.
- Familiarity with LoRA/adapters, distributed training, mixed precision.
- Proficiency with evaluation frameworks WER/sWER, Entity-F1, DER/JER, MOSNet/BVCC (TTS), PESQ/STOI (telephony), RTF/latency at P95/P99. and MLflow [logging.Frameworks](http://logging.Frameworks): Espnet, Speech brain, Nemo, Kaldi/K2, Livekit, Pipecat, Diffy
- Understanding of telephony speech characteristics, accents, and distortions.
- Collaborative mindset for cross-functional work with ML-ops and QA.

## Qualifications

- [B.Tech](http://B.Tech) / [M.Tech](http://M.Tech) / M.S. in Computer Science, AI, or related field.
- 4–7 years in applied ML; ≥2 years focused on speech recognition or synthesis.
- Experience with model deployment workflows preferred.

## About OutcomesAI

## Company Overview
- **One-liner**: OutcomesAI combines AI voice agents with licensed nurses to deliver scalable, safe, and cost-effective care delivery for health systems, virtual care providers, and pharmaceutical companies.
- **Entity Type**: Private (Seed Stage)
- **Headquarters**: Boston, Massachusetts, United States
- **Founded**: 2024
- **Founders**: Linda Finkel (CEO)

## Core Business
- **Primary Industry**: Healthcare IT / Hospitals and Health Care
- **Target Customers**: B2B – Health systems, virtual care providers, and pharmaceutical companies
- **Mission**: To reimagine care with AI that strengthens human connection — building safe, specialized AI that works alongside care teams, streamlining workflows, scaling clinical capacity, and improving outcomes without replacing the human touch.

## Products & Services
- **Glia® – AI Voice Agents**: AI-powered voice agents that handle routine patient interactions — answering calls, triaging symptoms, scheduling visits, delivering education, and managing follow-ups autonomously, with seamless escalation to licensed nurses when clinical judgment is required.
- **AI-Enabled Nurses**: Licensed nurses supported by AI-driven scribing, charting, and decision support, achieving up to 5× productivity while delivering safe, compassionate care.
- **Patient Access Solutions**: Automates scheduling, referrals, and care navigation.
- **Virtual Care**: Supports remote patient monitoring, hospital-at-home, and transition programs with a hybrid AI + nurse model.
- **Post-Acute & Transition Care**: Coordinates follow-ups and improves continuity of care.
- **Pharma & Specialty Care**: Nurse-led support for specialty therapies and chronic conditions (oncology, dementia, dialysis) including patient support programs and adherence outreach.

## Market Standing
- **Total Funding**: $10M (Seed Round, led by Sante Ventures, announced November 2025)
- **Key Metric**: 40–50% cost reduction and “up to 5× productivity” for nurses using the Glia platform
- **Notable Investors**: Sante Ventures (lead investor in Seed round)
- **Growth Signals**: 
  - 26 employees as of early 2026, with a distributed workforce across India, United States, and Singapore
  - Strong LinkedIn growth (+16.9% monthly follower growth)
  - Active hiring with 6 open positions as of early 2026
  - HIPAA and SOC 2 certified
  - AI follows evidence-based clinical protocols (Schmitt–Thompson triage protocols)

## Competitive Advantages
- **Hybrid AI + Nurse Model**: Unlike pure AI chatbots, OutcomesAI combines autonomous AI voice agents with licensed nurses for escalation — a unique safety differentiator in healthcare.
- **Clinical Safety Focus**: Built on evidence-based, protocol-driven care; passed over 25 medical certifications across nursing specialties.
- **Proprietary AI Engine (Glia®)**: Multi-modal AI optimized specifically for healthcare, developed with real nurses and care teams in real workflows.
- **Real-World Impact Metrics**: Proven 40–50% cost reduction and capacity scaling, delivering measurable results for health systems.

## Strategic Focus
- Currently expanding its AI-enabled nursing platform to more health systems and virtual care providers
- Aggressively building its engineering team, particularly in speech AI and ML-Ops (ASR/TTS/Speech LLM roles)
- Deepening capabilities in chronic disease management and pharma patient support programs
- Scaling the Glia platform across patient access, virtual care, and post-acute care segments

## Why Work Here
- **High-Impact Mission**: Work on real operational and clinical challenges — streamlining care delivery and making healthcare safer, smarter, and more human.
- **Cutting-Edge AI Work**: Opportunity to work on speech model deployment, ASR/TTS, and speech LLMs in a regulated healthcare context.
- **Clinical Collaboration**: Engineers work alongside licensed nurses and clinicians, designing AI that is actually used in care delivery.
- **International Team**: Distributed team across Boston (HQ), India (Bengaluru), and Singapore, with a strong engineering presence in India.
- **Growth Stage**: As a seed-stage startup with $10M in funding and active hiring, early employees have significant ownership and impact.
- **Technical Focus**: Majority of team is technical (47%), with roles spanning backend engineering, ML-Ops, ASR/TTS, and AI research.
- **Work Environment**: On-site roles in Bengaluru for engineering positions; Boston-based team likely hybrid/office.

## Sources
1. [outcomes.ai](https://outcomes.ai/)
2. [outcomes.ai/company](https://outcomes.ai/company)
3. [outcomes.ai/careers](https://outcomes.ai/careers)
4. [linkedin.com/company/outcomes-ai](https://linkedin.com/company/outcomes-ai)
5. [jobs.lever.co/outcomesai](https://jobs.lever.co/outcomesai)

## Other roles at OutcomesAI

- [Clinical Testing Manager](https://feeny.ai/job/clinical-testing-manager-outcomesai-remote-v2zz9sb803p4)
- [Tech Lead — ASR / TTS / Speech LLM (IC + Mentor)](https://feeny.ai/job/tech-lead-asr-tts-speech-llm-ic-mentor-outcomesai-bengaluru-q080gxkavgq3) — Bengaluru, India
- [Backend / ML-Ops Engineer — Speech Model Deployment & Inference Optimization](https://feeny.ai/job/backend-ml-ops-engineer-speech-model-deployment-inference-optimization-z73dn2wnbpm6) — Bengaluru, India