Machine Learning Engineer

IFM is hiring a Machine Learning Engineer in Abu Dhabi, United Arab Emirates. Level rates it ; you can apply on IFM.

Level's read on this job

Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include TensorFlow, fine tuning and computer vision.
Level classifies it as a mid-level role.
Level lists 43 other open roles at IFM.

AI in this role

TensorFlow

fine-tuningcomputer-visionnlpai-research

About the Institute of Foundation ModelsWe 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 RoleAs 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.

How we rate this

Machine Learning Engineer at IFM rates 99 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.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.

Key facts

Machine Learning Engineer is an open job at IFM.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Abu Dhabi.
The job was posted on July 2, 2025.
Seniority: mid.
Applications are handled by IFM. Apply on IFM

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningComputer visionNLPAI ResearchTensorFlow

Also common in machine learning engineer jobs at this level

Python PyTorch AWS Generative AI C++Kubernetes

Pay

Typical machine learning engineer job: $199k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a research question you investigated. What did you find?
Walk me through how you've used TensorFlow in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Fine-tuning, Computer vision, NLP, AI Research, and TensorFlow. 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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