Interested in this Research Engineer role at Duolingo?
Apply Now →About This Role
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 a Senior AI Research Engineer to join our Duolingo Video Call team. The ideal candidate will have a proven track record as an AI research engineer, with experience across various machine learning techniques including large language models, speech models, benchmarking, and/or personalization. They will have experience at multiple levels of the ML stack, including feature engineering, developing training data, fine\-tuning, reinforcement learning, quality evaluations, deployment, and monitoring. On the Video Call team, we're building AI systems that support the core learning mission of Duolingo, improving the learning experience and helping our learners build healthy, productive habits. Given the wide array 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 a variety of machine learning models, including large\-scale neural networks, speech recognition, and text\-to\-speech systems.
- Collaborate with cross\-functional teams to understand their needs, to align the models' outputs with company objectives.
- Participate in and influence strategic product and business decision making with members of the Language Learning leadership group.
- Stay up\-to\-date with the latest developments in machine learning 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, multimodal modeling, speech, 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 lead and inspire a team.
- 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.
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 [email protected].
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.
Salary Context
This $197K-$266K range is above the median for Research Engineer roles in our dataset (median: $207K across 63 roles with salary data).
View full Research Engineer salary data →Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 4,317 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Duolingo, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills in Demand for This Role
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $272,100 based on 227 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($232K) sits 15% below the category median. Disclosed range: $197K to $266K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and AI Engineering Manager ($244,000). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Duolingo AI Hiring
Duolingo has 2 open AI roles right now. They're hiring across Research Engineer, AI/ML Engineer. Based in New York, NY, US. Compensation range: $266K - $306K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.