Role Overview
Duolingo is hiring a Staff AI Research Engineer. This is a full-time role in New York. Part of Duolingo's Data Science hiring, posted 2 weeks ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.
Salary Context
Salary is not disclosed in this posting. Market median for Staff-level Data Science roles is $192k-$260k (based on 61 comparable listings). Many employers share specifics during the interview process or after an initial screen.
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Job description
Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!
At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems, running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful.
Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.
About the role...
We are looking for an experienced AI Research Engineer to join our Duolingo Monetization team. The ideal candidate will have a proven track record as an AI research engineer, with extensive experience across various machine learning techniques including large language models, multi-armed bandits, and more. They will have experience at all levels of the ML stack, including feature engineering, developing training data, fine-tuning, reinforcement learning, quality evaluations, deployment, and monitoring. On the Monetization team, we’re building AI systems to improve the learning experience while driving our business, including deploying our research into bandit models to balance revenue and retention. Given the broad set of AI domains, broad experience in AI/ML is highly desirable.
🧠 You will...
- Join a full-stack team of frontend, backend, and other AI Research engineers, fostering a collaborative and innovative work environment.
- Contribute to the development and training of bandit models and large-scale neural network models.
- Collaborate with cross-functional teams to understand their needs, to align the models’ outputs with company objectives.
- Participate in and help drive strategic product and business decision-making as a member of the Monetization leadership group.
- Stay up-to-date with the latest developments in machine learning, particularly in LLMs and bandits, and apply this knowledge to drive advancements in our projects.
- Mentor team members, providing guidance and support in their professional development.
- Ensure the delivery of high-quality, scalable, and efficient machine learning solutions.
✅ You have...
- Proven experience as an AI research engineer, for example, in 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 leadership and communication skills, with the ability to manage and inspire a team.
- Deep understanding of machine learning concepts, frameworks, and best practices.
The offered salary is dependent upon several factors, including work experience, skills, and internal peer comparisons. The posted range is subject to change in the future. For this role, base salary is supplemented by equity compensation. We encourage you to talk with your recruiter for more information related to compensation for this role!
Benefits: Take a peek at how we care for our employees' holistic well-being with our benefits here.
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Accommodations: We will do everything we can within reason to make sure that your interview takes place in an environment that fairly and accurately assesses your skills. If you need assistance or accommodation, please contact accommodations@duolingo.com.
Equal Employment Opportunity: Duolingo is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
Fraud Warning: Unfortunately, there is a rise in scammers pretending to be real Duolingo employees. Duolingo and our employees will never ask for your Social Security number, bank details, or passport info, and we’ll never ask you to deposit a check, purchase equipment, or exchange money during the interview process. Real Duolingo employees always use an email that ends in @duolingo.com or @recruiting.duolingo.com. Stay alert and double-check these details before sharing any information.
About Duolingo

Duolingo
duolingo.com
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Frequently Asked Questions
How do I apply for the Staff AI Research Engineer position at Duolingo?
Use the Apply button above to submit your application directly to Duolingo. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Staff AI Research Engineer position at Duolingo located?
This position is based in New York. Duolingo has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Staff AI Research Engineer at Duolingo earn?
Duolingo has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Staff AI Research Engineer role at Duolingo posted?
This role was posted on July 6, 2026 (16 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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