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Tech Lead, Machine Learning

5 Days ago • 4 Years + • Artificial Intelligence • $165,000 PA - $220,000 PA

Job Summary

Job Description

Ello seeks a Tech Lead, Machine Learning to oversee ML model development and deployment, lead the architecture design, and manage MLops. This role involves mentoring team members, setting standards for dataset management, and contributing to research. The ideal candidate will have strong software engineering and machine learning skills, experience with large language models, and a passion for impacting child development. Responsibilities include leading research, collaborating with other engineering teams, maintaining models and pipelines, and developing state-of-the-art ML systems for reading instruction, story generation, and interactive dialogue.
Must have:
  • 4+ years ML engineering/research experience
  • 2+ years building, scaling, and optimizing ML systems
  • Experience setting up MLops workflows
  • Experience deploying distributed pipelines on Kubernetes
  • Experience with large language models
  • Proficiency in applied mathematics and linear algebra
Good to have:
  • Experience setting up GPU clusters
  • Full-stack web development experience
  • Team leadership experience in ML
  • On-device systems experience
  • C/C++ or similar deployment experience
  • Mobile OS and I/O pipeline experience
  • Neural network optimization experience
  • Signal processing background
Perks:
  • Work at the cutting edge of AI and interactive learning
  • Collaboration with top researchers
  • Make a real impact on child development
  • Witness impact firsthand during playtests
  • Opportunity to work in a rapidly growing, well-funded company

Job Details

Engineering, Full-Time

San Francisco, CA

Salary range: $165,000 - $220,000 + 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’s 5-person Machine Learning team includes some of the world’s foremost experts in their areas. To give one example, our speech perception efforts are led by the co-authors of wav2vec. At Ello, they’ve built the world’s best child speech recognition system, beating Whisper. That ability to understand child speech reliably enables us to unlock the power of generative AI tools for early childhood learning. We work on a broad range of machine learning problems across NLP/NLU, image generation, and speech perception. 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.

About the role

As the Tech Lead on the ML team, you will work closely with the Co-Founder & CTO to lead the architecture design for all of our ML efforts. You will be in charge of MLops in collaboration with our Platform team and set good standards for your colleagues on critical design questions around dataset management, experiment tracking, and distributed training infrastructure. You will also get into the weeds as an IC, develop and review model and application code, and implement state-of-the-art machine learning systems for reading instruction, story generation, and interactive dialogue teaching.

You should have a strong background in software engineering and machine learning. We work on research problems on a production timeline. You will be successful in this role if you enjoy setting up scalable training systems and infrastructure from scratch and like shipping real-world products.

Most importantly, you are excited about the opportunity to make a real impact on child development at scale.

Responsibilities

  • Oversee the development and deployment of machine learning models to production environments

  • Lead by example, fostering a culture of excellence in architecture, coding, and model development 

  • Provide guidance, regular feedback, education, and mentoring to other members of the ML team

  • Monitor and maintain deployed models and data pipelines

  • Independently lead research work streams as part of Ello’s ML team

  • Lead collaboration with platform and Unity engineers as well as TPM and data team on data collection, pipeline design, model training, and deployment

  • Continuously learn and stay up to date with the latest advancements in machine learning engineering

Required Experience

  • 4+ years experience as an ML engineer/researcher working with modern Machine Learning toolkits (Python stack, very comfortable with PyTorch)

  • 2+ years of experience building, scaling, and optimizing ML systems

  • Experience setting up ML ops workflows and infrastructure from scratch in a startup environment (ideally in Terraform on AWS)

  • Production programming experience on a data-intensive project in distributed infrastructure

  • Experience deploying distributed data and training pipelines on Kubernetes

  • Experience with large language models

  • Experience writing high-performance, parallelized code

  • Applied mathematics and linear algebra proficiency at the level at which you can contribute to research discussions with a deeply technical team

  • Very accustomed to agile software engineering processes, git flow, etc.

Nice to have experience

  • Prior experience setting up GPU clusters (e.g. previously set up SLURM, or built multi-cloud model training pipelines with Infrastructure-as-Code)

  • Some familiarity with basic full-stack web development workflows and frontend API interaction

  • 2+ years of experience leading teams developing ML solutions

  • On-device systems experience

    • An understanding of low-level build pipelines and deployment experience in C/C++ or similar

    • Experience working with mobile operating systems and I/O pipelines in resource-constrained environments

    • Experience with optimizing neural networks to perform well on low-power mobile platforms (e.g. pruning, distillation, quantization)

  • Signal processing background

We look for candidates who

  • Have something to teach us

  • Want to do work they are proud of to ship products they are proud of

  • 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

  • Exemplify integrity in their actions, decisions, and communication

  • Want to build meaningful relationships at work

Here are some reasons to be a part of our team

  • Help lead a small but rapidly growing team of A+ engineers in a well-funded company

  • Work at the cutting edge of interactive learning and artificial intelligence

  • Stay plugged in with the research community while building real-world products

  • Do meaningful work supporting child development that you can witness firsthand during in-office playtests. Make an edit in your jupyter notebook this week, deploy it on-device in C++ next week, and watch it bring smiles to kids’ faces a day later

A note on immigration

We don’t shy away from sponsoring US visas and green card petitions. 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, H-1B transfers, etc. for Ello employees and retain top immigration counsel.

About Ello

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 offices in São Paulo, Brazil; Nairobi, Kenya; and New York.

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, we view diversity as a moral imperative and a competitive advantage. We do not discriminate on the basis of race, religion, skin color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We plan and structure our interviews to directly assess skills and experience. If you need any accommodations throughout the interview process, please reach out to jackie@ello.com.

Compensation Range: $165K - $220K

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About The Company

Building a 1:1 teacher was one of the original dreams of AI. It’s finally possible.

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

California, United States (On-Site)

San Francisco, California, United States (On-Site)

São Paulo, State Of São Paulo, Brazil (Hybrid)

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