Tech Lead, GenAI & Machine Learning

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 multimodal machine learning, NLP, 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 our ML and GenAI efforts. You will be successful in this role if you have a strong foundational understanding of AI models but ultimately care deeply about turning research outputs into magical real-world product experiences. Most importantly, you are excited about the opportunity to make a real impact on child development at scale.

Your role will bridge AI application development with third-party models and internal ML development leveraging our proprietary models and data.

• Machine learning: You should have foundational knowledge in ML. You will oversee 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 and implement state-of-the-art machine learning systems.

• AI Applications: You will lead the charge on bringing best practices to our AI-first product development process. You’ll scale our evaluation infrastructure for applications spanning complex use cases – reading instruction, story generation, and interactive dialogue-based teaching. You’ll design clean programming interfaces and build an internal SDK for our product engineering team. 

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 frontend 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 AI and machine learning engineering

Required Experience

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

• 2+ years of experience with GenAI product development (pipeline design, serving, prompt management, fine-tuning, evaluation, etc.), with some evidence shipping real world products using the most recent tools

• 3+ 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