AI/ML Engineer

Experience : 3+ years of experience building AI products in an engineering or research role. You’ve worked in environments that require you to take a high level of ownership.

Software engineering fundamentals: You take pride in writing clean Python code that others can build upon. You’re able to get up-to-speed quickly on unfamiliar code, work well with other engineers of varying backgrounds, and debug complex systems. You can make technical decisions with incomplete information while still maintaining high engineering standards.

Evaluation and product improvement: You’ve built and operated evaluation or measurement systems, such as AI evals. You can own the loop from ambiguous product quality questions, to concrete metrics and research plans, back to production improvements.

Research and experimentation: You’re comfortable with experimental thinking and reasoning through how to build systems around improving a non-deterministic product, while the underlying AI foundations shift. You can think empirically, but also make good calls in the gray area when needing to weigh conflicting signals and move quickly.

Machine learning foundations: You’re able to read recent ML papers and implement parts of the stack – you don’t need deep model training expertise, but you do need to understand how they work and how to evaluate them. You have sufficient proficiency in applied mathematics and linear algebra to contribute to research discussions.

AI-forward workflow: you have a working practice of leveraging AI in your engineering workflows, and an active curiosity in how AI is transforming work.

Public projects that demonstrate technical creativity

Strong product intuition — you can tell what's worth measuring and what isn't

Depth in low-latency inference at scale

Experience with model training

Familiarity with speech systems

Have something to teach us

Have an urge to make a real impact on child development at scale

Take initiative and full ownership of their work

Prefer open and direct communication grounded in empathy to beating around the bush

Want to build meaningful relationships at work

Ello’s 5-person applied ML team includes some of the world’s foremost experts in their areas. We work on a broad range of machine learning problems across agent reliability, learner adaptation, evaluation, and multimodal perception – including building the world's best child speech recognition system, designed by co-authors of wav2vec . We collaborate closely with advisors from Stanford and top industry research labs (on a weekly basis, not in some hands-off way). We work in-person out of our San Francisco office and we’re big believers in face-to-face collaboration.

If you already have work authorization in the US, we're open to sponsorship depending on your situation. Our CTO and CEO have each gone through their own immigration journeys and are familiar with the challenges. We have successfully secured O-1 visas for Ello employees and retain top immigration counsel.

Ello is a public benefit corporation on a mission to maximize the potential of all children. We’re currently around 45 people, headquartered in San Francisco with another office in Nairobi, Kenya.

Our team has deep expertise in artificial intelligence, K-12 education, and child development across institutions such as Stanford, Berkeley, Google, Apple, and more. We were part of Y Combinator’s W20 batch and are funded by world-class investors including Goodwater Capital, Homebrew, Reed Hastings, Common Sense Growth, Ravensburger, Project A Ventures, Reach Capital, Khosla Ventures, WndrCo, Visible Ventures, and K9 Ventures.

We’re a small, collaborative team that takes each other’s voices very seriously. Because our mission is to support all children, it is critical that our team is representative of the communities we work in; we place significant emphasis on ensuring diversity in our team and inclusion in our culture.

We feel enormously privileged to be one of the few companies that has the opportunity to take a shot at truly revolutionizing education with AI at this inflection point in technology. We don’t take it for granted, so we work quite hard to turn that vision into reality with urgency. We want to create an environment in which we can all be our best selves, use our strengths to take Ello forward, and develop our own skills. We want to have fun while working hard to do impactful things that we’re proud of – and we believe it’s possible to do both.

At Ello, diversity is a moral imperative and a competitive advantage. We do not discriminate based on race, religion, skin color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We plan and structure our interviews to assess skills and experience directly. If you need accommodations throughout the interview process, please contact recruiting@ello.com.