Technology Innovation Institute
VLM Engineer
Technology Innovation Institute is hiring a VLM Engineer. Level rates it ; you can apply on Technology Innovation Institute.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include PyTorch, LLM integration and AI evaluation.
- Level lists 15 other open roles at Technology Innovation Institute.
AI in this role
Technology Innovation Institute (TII) is a publicly funded research institute, based in Abu Dhabi, United Arab Emirates. It is home to a diverse community of leading scientists, engineers, mathematicians, and researchers from across the globe, transforming problems and roadblocks into pioneering research and technology prototypes that help move society ahead.
Artificial Intelligence and Digital Research Centre
As part of TII’s Artificial Intelligence Research Center, the Extreme-Scale Language Model team is developing and implementing innovative deep learning technologies with a broad range of applications, from Natural Language Processing to Perception and Vision. Our team has developed the Falcon models and is now planning to continue our journey into cutting-edge applied research in the topic of large language models.
Key Responsibilities:
- Vision Model Ablation Studies: Conduct comprehensive ablation studies on vision models to assess the impact of various components and configurations. Collaborate with researchers to analyze and report on the effectiveness of different model architectures and settings.
- Data Ablation Research: Partner with team members to perform data ablation studies, identifying optimal data types and structures for training vision-language models. Also, analyze the impact of different data inputs on model performance, particularly focusing on vision-language alignment.
- Model Evaluation: Develop and implement robust evaluation protocols for vision language models. Assess model performance across diverse benchmarks and real-world scenarios.
- Model Training and Optimization: Engage in model training, with an emphasis on integrating LLMs with vision models like CLIP. Technical
Skills Required:
- Expertise in machine learning, particularly in vision-language models and LLMs.
- Strong understanding of model architectures like CLIP and their application in vision language tasks.
- Proficiency in distributed training techniques and multi-GPU optimization.
- Experience with deep learning frameworks (e.g., PyTorch).
- Strong analytical skills for conducting ablation studies and evaluating model performance.
- Familiarity with dataset curation and processing for vision and language tasks.
Qualifications:
- PhD degree in deep learning.
- Proven track record of research and development in vision-language models. •
- Publication record in top-tier conferences is highly desirable
At TII, we help society to overcome its biggest hurdles through a rigorous approach to scientific discovery and inquiry, using state-of-the-art facilities and collaboration with leading international
institutions. Our rigorous discovery and inquiry-based approach helps to forge new and disruptive breakthroughs in AI, advanced materials, autonomous robotics, cryptography, digital security, directed energy, quantum computing and secure systems.
How we rate this
VLM Engineer at Technology Innovation Institute 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.
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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How have you integrated a large language model into a production application?
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What's a project where you used PyTorch hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: LLM Integration, AI Evaluation, NLP, and PyTorch. 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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