AI/ML Engineer
$166k - $230k • San Francisco, CA • FullTime
Posted 4mo ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Ello is building the world's first AI teacher to maximize the potential of every child. Our first product, Read with Ello, helps children learn to read by listening, adapting, and inspiring. We are scaling this success into a complete AI teacher for all children, combining language, speech, and memory for interactive learning worldwide. We operate at a fast pace, shipping weekly, testing directly with kids, and pushing the boundaries of AI in education. This role is on our product engineering and applied research team, working at the intersection of research and production to solve open-ended problems and deliver real-world products.
Responsibilities
- Define the impact of AI on children's education.
- Own AI systems and features end-to-end, from identifying product opportunities to shipping production improvements.
- Collaborate with learning experts and product engineers to build infrastructure for measuring educational quality, engagement, safety, latency, and behavior.
- Design and improve the agent harness that powers Ello’s tutoring experience, including decision-making for teaching, intervention, and adaptation.
- Develop learner profiling and adaptation systems to model each child and drive instructional decisions.
- Develop feedback loops and data flywheels to continuously improve product quality through usage, evaluation, and experimentation.
Requirements
- 3+ years of experience building AI products in an engineering or research role with a high level of ownership.
- Strong software engineering fundamentals, including clean Python code and debugging complex systems.
- Experience building and operating evaluation or measurement systems, such as AI evals.
- Comfort with experimental thinking and building systems for non-deterministic products.
- Ability to read recent ML papers and implement parts of the stack, understanding how models work and how to evaluate them.
- Proficiency in applied mathematics and linear algebra for research discussions.
- Working practice of leveraging AI in engineering workflows and curiosity about AI's transformation of work.