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Staff Machine Learning Engineer, Applied AI at Drive Health
Gilbert, Arizona, United States -
Full Time

Start Date

Immediate

Expiry Date

27 Jan, 26

Salary

0.0

Posted On

29 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, NLP, Technical Leadership, Python, Deep Learning, Collaboration, Voice AI, Speech-to-Text, Text-to-Speech, Generative AI, Healthcare Data, Algorithm Development, Team Management, Innovation, Empathy, Accuracy

Industry

Public Health

Description
What You’ll Do Lead high-impact AI initiatives, building and deploying advanced algorithms to tackle meaningful challenges in healthcare. Design and implement innovative techniques that ensure conversational voice agents are safe, accurate, empathetic, and reliable. Develop LLM-powered voice AI systems that deliver natural, human-like experiences. Partner closely with cross-functional teams to make decisions, move quickly, and deliver results in a fast-paced environment. Lead a talented team of ML engineers and scientists, fostering a culture of collaboration and excellence. Stay ahead of trends in generative AI, identifying and integrating the right technologies safely and effectively. What We’re Looking For 10+ years of hands-on experience in machine learning, including at least 6 years in NLP model development and evaluation. 3+ years of experience improving factual accuracy and reducing hallucinations using approaches like PEFT or grounding models. 3+ years of proven technical leadership experience, leading teams of 4–6 ML engineers/scientists, in a startup or fast-moving environment. Strong programming skills in Python and deep learning frameworks. A collaborative, self-motivated mindset with the ability to navigate ambiguity and drive progress from concept to execution. Bonus Points Experience with voice AI, including optimizing speech-to-text (STT) and text-to-speech (TTS) models. Familiarity with orchestration frameworks such as LangGraph. Experience working with healthcare data and understanding the unique challenges of regulated environments.
Responsibilities
Lead high-impact AI initiatives in healthcare by building and deploying advanced algorithms. Design and implement techniques for conversational voice agents to ensure they are safe, accurate, empathetic, and reliable.