Time since we first saw it
Day 204
Up longer than most. Similar jobs usually come down between day 6 and day 70.
From 4,523 similar postings that came down. Coming down is not always a hire.
Research Engineer/Scientist - Speech/Audio Machine Learning
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: onsite
From the employer’s posting- Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDevelop novel neural architectures for low-latency speech-to-speech translation and generation
Design custom objective functions to optimize prosody, intelligibility and naturalness
Run large-scale training runs and ablation studies on architecture and tokenization
Build internal benchmarks using objective metrics and human MOS testing
From the employer’s posting
Develop novel neural architectures for low-latency speech-to-speech translation and generation
Design and implement custom objective functions to optimize prosody (emotions, intelligibility, naturalness).
Conduct large-scale training runs, performing ablation studies on model architecture and tokenization strategies.
Establish rigorous internal benchmarks using both objective metrics (WER, MCD) and subjective human-in-the-loop (MOS) testing.
What you’ll bring
All qualificationsCore experience
- PhD or MSc in Computer Science, focused on Deep Learning, Signal Processing, or Computational Linguistics
- Published research in top-tier venues such as NeurIPS, ICLR, ICASSP, or Interspeech
Qualification wording
PhD or MSc in Computer Science with a focus on Deep Learning, Signal Processing, or Computational Linguistics.
Published work in top-tier venues (NeurIPS, ICLR, ICASSP, Interspeech).
Education & alternatives
Qualifications - PhD or MSc in Computer Science with a focus on Deep Learning, Signal Processing, or Computational Linguistics. - Record of Research: Published work in top-tier venues (NeurIPS, ICLR, ICASSP, Interspeech).
About Ifm-Us
We are a dedicated research lab for building, understanding, using, and risk-managing foundation models.
In the employer’s words · Read in context
Posting record
Report an errorOpen 6 monthsWe first saw this posting 204 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 15, 2026204 days ago
- Recorded sightings
- 144
- Last seen by us
- Nov 5, 2026
- Employer says posted
- Dec 30, 2025
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Ifm-Us is hiring
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Its jobs tend to stay up a long time
Your next step
Check the employer’s posting for the current role and application details.
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About the Institute of Foundation Models
We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.
As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.
The Role
As a Research Scientist specializing in speech/audio machine learning, you will contribute to the design and training of SoTA end-to-end neural speech models. You will be responsible for developing the core intellectual property, moving beyond cascaded ASR → TTS systems toward native audio-to-audio multimodal architectures.
Key responsibilities
- Architectural Design: Develop novel neural architectures for low-latency speech-to-speech translation and generation (e.g., Diffusion, Flow-matching, Transformer-based audio LLMs).
- Loss Function Engineering: Design and implement custom objective functions to optimize prosody (emotions, intelligibility, naturalness).
- Experimental Iteration: Conduct large-scale training runs, performing ablation studies on model architecture and tokenization strategies.
- Evaluation Frameworks: Establish rigorous internal benchmarks using both objective metrics (WER, MCD) and subjective human-in-the-loop (MOS) testing.
Qualifications
- PhD or MSc in Computer Science with a focus on Deep Learning, Signal Processing, or Computational Linguistics.
- Record of Research: Published work in top-tier venues (NeurIPS, ICLR, ICASSP, Interspeech).
Employment type
Full-time
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Paris
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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