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.
Machine Learning Engineer
- 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 postingAdapt research technologies and integrate them into the codebase
Build systems for the model lifecycle: data preprocessing, pre-training, post-training, evaluation
Join or lead design reviews to choose among available technologies
Review other developers' code for style, accuracy, testability and efficiency
Triage and debug product or system issues across hardware, network and services
From the employer’s posting
Collaborate with Research teams to understand technologies, adapting and integrating them into codebase.
Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing, pre-training, post-training, evaluation and so on, especially foundation models.
Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Education & alternatives
Academic Qualifications - Minimum: Bachelor’s degree or equivalent practical experience. - Preferred: Master's degree or PhD in Computer Science or related technical field.
- Minimum: Bachelor’s degree or equivalent practical experience. - Preferred: Master's degree or PhD in Computer Science or related technical field. Professional Experience - Minimum
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
- 139
- Last seen by us
- Nov 5, 2026
- Employer says posted
- Jul 2, 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
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- TensorFlow
Where the posting names them
- 2 years of experience with data structures or algorithms in either an academic or industry setting. - 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing. - Excellent problem-solving and troubleshooting skills to address complex technical challenges.
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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 Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world challenges, pushing the boundaries of artificial intelligence research. You will collaborate with cross-functional teams to deploy scalable solutions, contributing to MBZUAI’s mission of driving impactful AI discoveries and positioning the institution as a leader in the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine learning models, while supporting the development of transformative AI tools that can influence industries worldwide.
Key Responsibilities
- Collaborate with Research teams to understand technologies, adapting and integrating them into codebase.
- Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing, pre-training, post-training, evaluation and so on, especially foundation models.
- Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.
- Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.
Academic Qualifications
- Minimum: Bachelor’s degree or equivalent practical experience.
- Preferred: Master's degree or PhD in Computer Science or related technical field.
Professional Experience - Minimum
- 3 years of experience in software engineering, including experience with Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Computer Vision.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
- 2 years of experience with data structures or algorithms in either an academic or industry setting.
- 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
- Excellent problem-solving and troubleshooting skills to address complex technical challenges.
- Effective communication and collaboration skills to work with cross functional teams.
Professional Experience - Preferred
- 2 years of experience with improving performance during large scale data processing
- Hands-on experience with LLM algorithms, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).
- Excellent data analysis skills.
Employment type
Full-time
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Abu Dhabi
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.