AI Frameworks Engineer

Description

Job Details:

Responsibilities

• As an AI Frameworks Engineer, you will design, develop, and optimize AI frameworks, including Intel's OpenVINO Toolkit and external frameworks like TensorFlow and PyTorch. You'll focus on building scalable solutions for generative AI and deep learning, transforming computational graphs, and implementing distributed algorithms to accelerate AI performance across Intel hardware. Your expertise will tackle real-world challenges, enabling high-performance inference solutions that impact industries worldwide.
• Business Group
• The Software Group at Intel is focused on advancing AI solutions across diverse industries, empowering developers to create cutting-edge applications for edge and cloud environments. As part of this team, you will contribute to enabling seamless and efficient AI experiences, ensuring Intel continues to drive innovation in deep learning, generative AI, and machine intelligence.
• Develop and optimize AI frameworks like OpenVINO and external frameworks such as TensorFlow and PyTorch.
• Implement distributed algorithms, including model/data parallel frameworks and dataflow-based communication for deep learning.
• Transform computational graph representations and develop machine learning primitives in mathematical libraries.
• Profile distributed deep learning models to identify performance bottlenecks and propose optimization solutions.
• Optimize code across various computing hardware backends.
• Collaborate with machine learning researchers and framework teams to integrate AI advancements efficiently.

Requirements

• Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, Mathematics, or related field with 4+ years of experience OR Master's degree with 3+ years of experience.
• Proven expertise in C++ programming, including debugging, performance analysis, and modern software design techniques.
• Demonstrated understanding of multithreading concepts and developing thread-safe code.
• Strong skills in data structures, algorithms, and compiler technologies.
• Hands-on experience with numerical modeling, high-performance computing, or computer vision.
• Preferred Qualifications
• Experience with generative AI models (e.g., Transformers, Diffusion models).
• Knowledge of model optimization techniques (e.g., quantization, pruning).
• Experience in deep learning frameworks like PyTorch, TensorFlow, or Hugging Face Transformers. Familiarity with OpenVINO Toolkit or similar inference runtimes.
• Background in performance analysis and optimization techniques.
• Experience contributing to open-source projects.
• Strong problem-solving skills and the ability to work collaboratively in diverse environments.
• We invite you to join Intel's team of visionaries and innovators, where your contributions will play a pivotal role in shaping the future of AI and advancing groundbreaking technologies.
• Job Type:
• Experienced Hire
• Shift:
• Shift 1 (Ireland)
• Primary Location:
• Ireland, Leixlip
• Additional Locations:
• Posting Statement:
• Position of Trust
• N/A
• EU Salary
• We offer a total compensation package that ranks among the best in the industry.
• Annual Salary Range for this job which could be performed in Ireland is: ‏76,900.00 € - ‏142,100.00 €&xa;&xa;The compensation range displayed in this posting reflects the minimum and maximum target compensation for this position. Within this range, individual pay is determined by job related skills, experience, and relevant education, training. As part of our total compensation approach, the final offer may include additional pay components and benefits. Your recruiting team will share the confirmed base salary along with any applicable total compensation elements upon employment offer delivery.
• Work Model for this Role
• This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. Job posting details (such as work model, location or time type) are subject to change.