Sr. Data Scientist - AI Voice
$113,800–$154,525 year
On-siteMassachusetts, United States
Job Summary
Build and deploy real-time conversational voice agents across the speech stack, including speech-to-text, LLM reasoning, and text-to-speech. Develop simulation capabilities to generate and role-play patient conversations at scale, covering edge cases beyond manual testing. Design and train deep neural networks from the ground up, fine-tuning language models on clinical and longitudinal healthcare data. Establish evaluation pipelines measuring model output for accuracy and consistency, while red-teaming AI agents to surface failure modes before production. Partner with clinical, product, and engineering teams to define technical work and mentor junior members. This hands-on role reports to the VP of AI, focusing on developing the voice AI and model capabilities behind Tom, the AI-enabled primary care platform.
Required Qualifications
- Bachelor's degree with quantitative major (e.g. statistics, mathematics, economics, and actuarial science) or equivalent
- 5+ year of relevant data science, machine learning, or applied AI experience, or the knowledge, skills, and abilities to succeed in the role
- Must-have hands-on experience building and deploying production voice or conversational AI systems — speech and speech-to-speech, working with real audio in live environments, not text-only NLP or chat
- Must-have demonstrated experience training neural networks from scratch and fine-tuning language models, with the ability to explain different training approaches and when each applies
- Proven track record of shipping, scaling, and hardening AI systems in production
- Strong programming skills in Python and fluency with modern deep learning frameworks (PyTorch, TensorFlow)
- Working knowledge of real-time audio infrastructure and telephony integration
- All personnel who interact with at-risk members or prospects are required to have completed, at a minimum, the initial series of an approved COVID-19 vaccine
Desired Qualifications
- Master's or PhD in a quantitative or scientific discipline
- Google Cloud Platform (GCP) experience
- Healthcare or other regulated-domain experience, including familiarity with clinical data standards such as FHIR
- Experience building voice models or conversational agents at an AI lab or voice-first platform
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