Twin Health

Senior AI Engineer

Twin Health

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $200,000 - $220,000 per year

Job Level

Senior

Tech Stack

PythonSQL

About the role

  • Drive the end-to-end lifecycle of AI products, from ideation and prototyping to development, deployment, and optimization
  • Apply advanced techniques like advanced Prompt Engineering, conversational AI agents, deep learning, and personalized recommendations to create “N of 1” solutions that adapt to individual needs
  • Build and improve ML models to drive behavior change to achieve sustained improvements in metabolic health for a diverse member base across diabetes, weight loss, etc.
  • Influence product roadmap by deeply understanding member behavior and preferences through continuous data analysis
  • Collaborate cross-functionally with our clinical, medical research, business analytics, and engineering teams to design end-to-end AI-powered experiences for our members and clinical teams and achieve metrics-driven impact
  • Ship AI features used by members to improve their health every day
  • Additional duties as assigned

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Statistics, or a related field; PhD a plus
  • 5+ years of industry experience developing AI and Machine Learning systems in production
  • Experience building consumer facing features a plus
  • Experience creating applications leveraging LLMs, Generative AI, advanced Prompt Engineering, RAG, and iterative AI evals
  • Experience building, deploying, and optimizing ML models using advanced techniques like deep learning neural networks
  • Experience with Voice AI or specialized Language Models (VLMs, multi-modal, etc) would be a plus
  • Proficiency in programming with Python and complex analysis of large datasets using technologies like SQL, Snowflake, etc.
  • This remote opportunity is available to US based persons. Applicants must be authorized to work for any employer in the U.S.
  • Previous experience in healthcare preferred but not required
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