# Senior AI Engineering Manager

**Company:** [Duolingo](https://hotfix.jobs/companies/duolingo)
**Location:** New York, NY, Pittsburgh, PA
**Role:** Engineering Management
**Salary:** $221k – $331k/yr
**Experience:** 8+ years
**Skills:** Machine Learning, LLMs, Reinforcement Learning, Fine-Tuning, Feature Engineering, Recommender Systems, Experimentation, Python, Neural Networks, Model Deployment
**Posted:** 2026-06-09

> Lead and mentor a multidisciplinary AI research engineering team building core language learning ML systems at Duolingo. Requires proven AI/ML leadership, large model training experience, and an advanced degree or equivalent.

## Job Description

## Responsibilities
- Manage a full-stack team of frontend, backend, and AI Research engineers, fostering a collaborative and innovative work environment.
- Contribute to the development and training of a variety of machine learning models, including large-scale neural networks.
- Collaborate with cross-functional teams to understand their needs and align model outputs with company objectives.
- Participate in and help drive strategic product and business decision-making as a member of the Language Learning leadership group.
- Attract, grow, and retain diverse engineering talent; provide clear expectations, coaching, and career development, and build a healthy, inclusive team culture.
- Stay up-to-date with the latest developments in machine learning and apply this knowledge to drive advancements in projects.
- Mentor team members, providing guidance and support in their professional development.
- Ensure the delivery of high-quality, scalable, and efficient machine learning solutions.

## Requirements
- Experience leading, managing, and building a team of software engineers, with demonstrated ability to hire, develop, and retain talent.
- Proven experience as an AI research engineer (e.g., LLMs, bandits, computer vision, or related fields).
- Strong background in training and fine-tuning large models in an applied setting.
- Advanced degree in Computer Science, Engineering, or a related field with a focus on machine learning or artificial intelligence, or equivalent experience.
- Excellent communication and stakeholder management skills across engineering, product, design, and data; clear written specs and status updates.
- Technical depth sufficient to guide architecture and implementation trade-offs, evolve quality standards, and mentor engineers on best practices.
- Deep understanding of machine learning concepts, frameworks, and best practices.

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