Senior Product Engineer (ML & Mobile)

Engineering, full-time

San Francisco (Relocation assistance available)

Salary range mid-senior: $180,000 - $215,000 + Equity

At Ello, our mission is to maximize the potential of all children. Our first product, Read with Ello, is an AI reading teacher that listens to children read out loud. Ello uses speech recognition to help them when they get stuck, makes up stories using generative AI, and inspires a love for reading.

We’re now building on the success of Read with Ello and putting together the pieces of the world’s first complete AI teacher for all children. Together, we believe we can close the primary school education gap worldwide.

Ello has been recognized on Fortune’s “Change the World” and Time’s 2024 Best Inventions lists. We are well-funded, backed by world-class investors, and ready to recruit new talent to help us achieve our vision.

Who you’ll be joining

Ello is a rapidly growing, series A startup focused on revolutionizing the way children learn and interact with technology. You will work directly with Ello’s Co-founder & CTO, Catalin Voss, on a small team (<10) of engineers, learning designers, and PMs to develop new products. You’ll be surrounded by a team of A+ engineers and you’ll work with some of the foremost experts in ML to productionize models and build new product experiences. We work in-person out of our San Francisco office and we’re big believers in face-to-face collaboration.

About the role

We’re looking for a strong Sr. Product Engineer, New Products to independently own the build-out of learning activities as part of Ello’s next-generation AI tutoring apps. You will bridge the gap between product development and engineering to own features from conception to playtest, at times acting as your own product manager, and at times collaborating closely with our product team. You’ll be part of a small team that is responsible for bringing Ello’s tutoring AI to life through agent control, character development, and game interactions. You pay attention to the details and thrive building products that delight users.

You can work full-stack and across multiple programming languages, build chains, etc. Learning yet another language doesn’t feel like a daunting task at this point. You have experience with or a demonstrated curiosity for GenAI pipelines. On the backend, you’re able to write performant Python code and deal with complex I/O pipelines. On the frontend, you’re able to take an existing component library and build a rough UI from scratch (Flutter & React) without a designer or implement pixel-perfect layouts in collaboration with a designer.

We welcome candidates from all backgrounds – mobile engineering, machine learning, or design & product – but we prioritize strong technical foundations and demonstrated execution speed in shipping. As an ideal candidate, you’ll have built and shipped software products end-to-end in the past, for example through an initiative you championed at a prior job, through an impressive side project, or as the founder of your own company. We’d love to hear about those in the interview process!

Responsibilities

• Own and build features end-to-end, from concept to delivery

• Build agent-based AI pipelines, interfacing with ML engineers working on core models (e.g. our child speech recognition pipeline)

• Serve as a bridge between product design and engineering, moving fluidly between UX/UI and technical problem-solving

• Develop and integrate front-end components for mobile and web platforms, leveraging existing design systems and brand guidelines

• Do whatever it takes to go from product conception to playtest

Required Experience

• Engineering:

  • Excellent production-grade engineering & debugging skills across backend, ML, and mobile frontend

  • Experience with at least one of Flutter, native Android development in Java/Kotlin, or iOS development in Swift/ObjC

  • Experience with ML tooling and GenAI tools (you don’t need to be a linear algebra beast designing your own models, but you should understand how multimodal models work and communicate with ML engineers in their language)

  • Some experience with GenAI models & pipelines, including human eval infrastructure

  • Familiarity with Git flow, etc.

  • Basic data science skills (enough to analyze your own product insights)

  • Familiarity with basic infrastructure setup, continuous integration, and production release workflows

• Design & Product:

  • Very high level of attention to detail. For example, yo