Staff AI Engineer
New
T
Twin HealthDigital Health
Remote, USAFull-TimeStaff
Salary$250,000-$265,000 annually
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Job Details
- Experience
- 8+ years
- Required Skills
- PythonMachine LearningCI/CDDeep LearningPrompt EngineeringGenerative AI
Requirements
- 8+ years of industry experience developing AI and Machine Learning systems in production.
- Track record of leading technical initiatives that span multiple teams or systems.
- Deep software engineering fundamentals: testing, CI/CD, system design, code review.
- Demonstrated experience designing evaluation infrastructure and shared tooling for LLM-based systems.
- Proven experience setting technical direction and engineering standards at an organizational level.
- Experience creating and scaling applications leveraging LLMs, Generative AI, advanced Prompt Engineering, RAG, and iterative AI evals.
- Track record of mentoring senior engineers and influencing technical decisions beyond your own project.
- Proficiency in Python and software engineering best practices.
- Bachelor's or Master's degree in Computer Science, Statistics, or a related field.
Responsibilities
- Design and build the core architecture for AI systems spanning multiple product areas, ensuring coherence and reuse across different applications.
- Set the technical bar for the org: evaluation frameworks, testing philosophy, CI/CD for model behavior, and shared infrastructure used across multiple teams.
- Identify and resolve systemic engineering gaps before they become team-wide problems.
- Take direct ownership of the hardest, most ambiguous technical problems on the team and build the solution end-to-end.
- Build and ship conversational agents, deep learning models, and personalization systems that require novel technical approaches.
- Improve AI/ML systems and services to drive behavior change and sustained metabolic health improvements.
- Raise the technical level of the team through code review and design review.
- Partner with product, engineering leadership, and clinical/research teams to turn ambiguous goals into technical designs.
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