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# Research Engineer

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/elevenlabs.md)Share24 Sep 2026Published46Listing views1Application actions24 Oct 2026Apply before  Opportunity details

## About this role.

AI SummaryElevenLabs is hiring a Research Engineer to advance frontier audio AI models used across its voice and generative media products. The role centers on training and post-training machine-learning models, improving datasets and architectures, and developing rigorous benchmarks and evaluations. Candidates should bring at least three years of AI experience and evidence of solving difficult technical problems through projects, designs, GitHub work, or publications. This is a globally remote, high-velocity role emphasizing independent experimentation, technical excellence, and measurable model-quality improvements.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

4/5IndependentCollaborative

AI insightThe position requires advanced applied ML research skills, including model training, data curation, architecture iteration, and scientifically rigorous evaluation. The high-velocity environment and expectation to independently explore novel concepts make it especially demanding.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate$185,000US market range$150k–$230k0$253k

AI insightNo actual salary is disclosed, so these are estimated US-market annual base-salary figures in USD for a Research Engineer with 3+ years of AI/ML experience at a well-funded frontier AI company. Total compensation may be higher when equity and other benefits are included.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[machine learning](https://jobicy.com/jobs?search_keywords=machine%20learning.md)[deep learning](https://jobicy.com/jobs?search_keywords=deep%20learning.md)[audio AI](https://jobicy.com/jobs?search_keywords=audio%20AI.md)[generative AI](https://jobicy.com/jobs?search_keywords=generative%20AI.md)[model training](https://jobicy.com/jobs?search_keywords=model%20training.md)[post-training](https://jobicy.com/jobs?search_keywords=post-training.md)[data curation](https://jobicy.com/jobs?search_keywords=data%20curation.md)[model evaluation](https://jobicy.com/jobs?search_keywords=model%20evaluation.md)[benchmarking](https://jobicy.com/jobs?search_keywords=benchmarking.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)

Sample interview questionsDescribe a machine-learning model you improved substantially. What did you change, and how did you measure the result?I would explain the baseline, identify the limiting hypothesis, and describe the experimental changes such as data filtering, objective changes, architecture updates, or training-schedule tuning. I would report statistically meaningful offline metrics, slice-level results, and, where applicable, production or human-evaluation outcomes.

How would you determine whether a new audio model iteration is genuinely better than the current model?

I would define a versioned evaluation suite covering representative tasks, languages, acoustic conditions, and known failure modes. I would combine automated metrics with blinded human preference tests, analyze regressions by slice, and set release thresholds that prevent aggregate gains from masking important quality declines.

What is your approach to improving the quality of a large training dataset?

I begin by defining quality dimensions such as correctness, diversity, licensing, metadata completeness, and relevance to target use cases. I then use automated filters and deduplication, targeted manual audits, error taxonomy analysis, and iterative sampling to validate that data changes improve downstream model behavior.

How do you handle exploratory research when the best technical direction is uncertain?

I convert uncertainty into a set of falsifiable hypotheses and run the smallest experiments that can distinguish among them. I document assumptions, controls, metrics, and outcomes, then prioritize follow-up work based on expected impact, confidence, computational cost, and strategic relevance.

Tell us about a time you worked autonomously on a difficult technical problem.

I would describe how I scoped the problem, gathered context, created an experiment plan, and communicated concise progress updates without needing constant direction. I would emphasize the artifact produced, the evidence supporting the final decision, and what I learned when initial approaches did not work.

### About ElevenLabs

ElevenLabs is an AI research and product company transforming how we interact with technology.

We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses – from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world’s most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We’ve raised $781M in funding and our last valuation was $11B – multiples of 11, always.

We have expanded from voice into three main platforms:

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ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.

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ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.

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ElevenAPI gives developers access to our leading AI audio foundational models.

Everything we do is the result of the creativity and commitment of our team – builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you.

### How we work

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High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.

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Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.

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AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.

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Excellence everywhere: Everything we do should match the quality of our AI models.

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Global team: We prioritize your talent, not your location.

### What we offer

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Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.

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Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact – beyond your immediate role and responsibilities.

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Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend.

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Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose.

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Annual company offsite: Each year, we bring the entire team together in a new location – past offsites have included Croatia and Italy.

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Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend.

### About the role

We are looking for a Research Engineer to join the research team at ElevenLabs. You’ll work at the frontier of audio AI, shaping the models behind products used by millions of people. You will thrive in this role if you enjoy:

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Training state-of-the-art models – across any modality.

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Pushing existing models further through post-training, data curation, architectural improvements, and novel training paradigms.

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Designing rigorous benchmarks and evaluations that tell us whether a new model iteration is genuinely better – and why.

### Requirements

We do not require any formal certifications or degrees. Instead, we are seeking enthusiastic engineers who can showcase solving impressively hard problems with artifacts such as past projects, designs, or GitHub contributions. Ideally you bring:

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3+ years of experience in the field of AI, with an emphasis on implementing, training, and improving machine learning models.

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Demonstrated capacity to autonomously evaluate novel concepts or enhance existing machine learning projects, potentially contributing to published work.

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Experience conducting exploratory research to improve the quality of gathered data.

### Location

This role is remote and can be executed globally. If you prefer, you can work from our offices in London, New York, San Francisco, and Warsaw.

#LI-Remote

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Show more

[Apply now >](https://jobicy.com/jobs/154024-research-engineer.md)

>  Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md)

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