Staff AI Research Engineer
Duolingo is hiring a Staff AI Research Engineer in Pittsburgh, United States. It pays $221k-$331k a year and Level rates it ; you can apply on Duolingo.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include fine tuning, computer vision and AI research.
- Level classifies it as a lead role.
- Level lists 59 other open roles at Duolingo.
AI in this role
Lead AI research and development of machine learning and bandit models for monetization and user retention.
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!
Salary Range: $220,800—$331,200 USDBenefits: 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.
By applying for this position your data will be processed as per the Duolingo Applicant Privacy Notice.
How we rate this
Staff AI Research Engineer at Duolingo rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where large language models was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, Computer vision, AI Research, Machine learning, and Large Language Models. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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