Machine Learning Engineer — Pre-training (LLM)

AI in this role

Build and scale distributed machine learning infrastructure to support large-scale pre-training of foundational language models.

deepspeedfsdpfairscalehorovod

distributed-trainingllmpre-traininginfrastructure

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 Role

We’re looking for a distributed ML infrastructure engineer to help extend and scale our training systems. You’ll work side-by-side with world-class researchers and engineers to:

Extend distributed training frameworks (e.g., DeepSpeed, FSDP, FairScale, Horovod)
Implement distributed optimizers from mathematical specs
Build robust config + launch systems across multi-node, multi-GPU clusters
Own experiment tracking, metrics logging, and job monitoring for external visibility
Improve training system reliability, maintainability, and performance

Much of the work will support large-scale pre-training, and pre-training experience is required. Strong infrastructure and systems experience is what we value most.

How we rate this

Machine Learning Engineer — Pre-training (LLM) at IFM rates 90 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. Open the description and count.

Key facts

Machine Learning Engineer — Pre-training (LLM) is an open job at IFM.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $150k-$450k a year.
The role is based in Sunnyvale, CA.
The job was posted on October 5, 2026.
Applications are handled by IFM. Apply on IFM

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Distributed TrainingLLMPre TrainingInfrastructureDeepspeedFsdpFairscaleHorovod

Questions you could be asked

Tell me about a project where distributed training was part of your work. What did you do?
Tell me about a project where llm was part of your work. What did you do?
Tell me about a project where pre training was part of your work. What did you do?
Tell me about a project where infrastructure was part of your work. What did you do?
Walk me through how you've used Deepspeed in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Distributed Training, LLM, Pre Training, Infrastructure, and Deepspeed. 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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