Research, design, and implement sustainability features to quantify and minimize the environmental impact of large-scale AI model training and inference.
Collaborate with hardware and software engineers to ensure efficient model deployment on custom silicon solutions.
Explore new techniques for improving model footprint, model throughput, and hardware utilization.
Develop and implement distributed scheduling strategies for carbon-aware large-scale model deployments across high-performance computing infrastructures.
Conduct performance benchmarking and profiling of ML workloads on custom accelerators.
Stay up to date with advancements in deep learning, sustainability, and AI hardware to bring innovative ideas into Openchip’s AI strategy.
Participate in technical discussions and contribute to Openchip’s AI research and development roadmap.
Requirements
MSc or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
Publication record is a plus.
Hands-on experience in training and deploying AI models, particularly LLMs or equivalent large architectures.
Strong programming skills in Python and proficiency with ML frameworks, such as PyTorch or TensorFlow.
Strong knowledge of deep learning model optimization techniques, such as pruning, quantization, knowledge distillation, and reasoning optimization.
Experience in sustainability topics is highly desirable.
Familiarity with hardware/software co-design principles and methodologies is considered a plus.
Fluent in English is a must; knowledge of additional European languages (German, Dutch, Spanish, French, or Italian) is a plus.
Benefits
Join an innovative team and experience company growth.
We believe in investing in our employees and providing them with opportunities for growth and career development.
Work in a hybrid environment with flexible scheduling.
We offer a remuneration that values your experience.
A chance to work at one of the most transformative AI and silicon engineering companies in Europe.
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