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Duolingo

Staff AI Research Engineer

Duolingo is hiring a Staff AI Research Engineer in New York and Pittsburgh, United States. It pays $221k-$331k a year and Level rates it ; you can apply on Duolingo.

Level's read on this job

  • Level rates this role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions fine tuning, speech and AI research among its tools and skills.
  • Level classes it as a lead role.
  • Duolingo has 54 other open roles on Level.
  • Posted in the last few days.

AI in this role

fine-tuningspeechai-research

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 Speech team. The ideal candidate will have a proven track record as an AI research engineer, with experience across various machine learning techniques, and a particular focus on speech modeling: ASR, TTS, speech-to-speech models, audio tokenization, and more. They will have experience at all levels of the ML stack, including feature engineering, developing training data, fine-tuning, reinforcement learning, benchmarks and evaluations, deployment, and monitoring. On the Speech team, we’re training custom models to understand the speech of non-native learners, working closely to support product teams working on features like Video Call and the learning path.

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 speech 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 Speech leadership group.
  • Stay up-to-date with the latest developments in machine learning, particularly in speech models, 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 speech recognition, TTS, LLMs, 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 USD

Benefits: Take a peek at how we care for our employees' holistic well-being with our benefits here.

Job Alerts: Sign up for job alerts here.

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 92 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.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

Fine-tuningSpeechAI Research

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. What have you built with speech recognition or text-to-speech, and where did it break?
  3. Tell me about a research question you investigated. What did you find?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Fine-tuning, Speech, and AI Research. 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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