Join Axelera AI as a Senior AI Research Engineer to develop and optimize multimodal AI models for real-time inference. Collaborate with cross-functional teams to integrate AI models into the platform. Stay up-to-date with the latest research in multimodal AI and propose new techniques to push the boundaries of generative AI.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Company Overview
Axelera AI is a European, high-growth Series B startup revolutionizing the AI landscape with our in-memory computing platform. We specialize in creating AI hardware and software optimized for high-performance inference, catering to cutting-edge use cases across high-end edge computing, embodied AI, and server-side AI deployments. We are looking for passionate, innovative research engineers to join our team and help drive the future of AI.
Role Overview
We are seeking a Senior AI Research Engineer with expertise in developing and optimizing multimodal AI models. The role will be central to advancing our platform’s capabilities in inference for Generative AI, working on state-of-the-art models that integrate multiple data modalities (e.g., text, vision, and audio) for a broad range of applications.
This is an exciting opportunity to work at the intersection of advanced machine learning, in-memory computing, and high-performance AI inference on cutting-edge hardware architectures.
Responsibilities:
- Model Development: Design, develop, and optimize multimodal AI models for real-time, high-efficiency inference across a variety of deployment environments (edge, server-side, and embodied AI).
- Collaboration: Work closely with cross-functional teams, including AI researchers, hardware engineers, and software engineers to integrate AI models into the broader platform.
- Scalability and Optimization: Focus on optimizing models for memory efficiency, low-latency inference, and high throughput.
- Innovation: Stay up-to-date with the latest research in multimodal AI, proposing and implementing new techniques to push the boundaries of what's possible in generative AI.
- Deployment & Testing: Implement best practices for model testing, deployment, and continuous improvement to ensure models scale effectively in production environments.
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- Experience: Proven experience (for all levels) in developing and deploying multimodal models, including text, image, and/or audio data.
- Technical Skills:
- Strong background in deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
- Proficiency in natural language processing (NLP), computer vision (CV), and speech processing techniques.
- Experience with model optimization techniques (e.g., quantization, pruning, distillation).
- Familiarity with distributed computing, in-memory computing platforms, or high-performance computing.
- Knowledge: A strong understanding of the latest advancements in AI/ML research, particularly in generative models (e.g. transformers and diffusion models).
- Collaboration & Communication: Ability to work in a highly collaborative, fast-paced startup environment and communicate complex technical concepts clearly.
- PhD or advanced degree in Computer Science, Machine Learning, AI, or related fields.
- 5+ years of post-graduation relevant work experience.
- Experience in deploying models on edge devices or in-memory computing systems.
- Familiarity with model deployment frameworks like TensorRT, ONNX, or similar.
- A passion for solving real-world challenges with AI in dynamic, high-performance environments.
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This position is based in Belgium (on-site/hybrid) or Italy (on-site/hybrid/remote) & we support relocation to Leuven, Bologna, Florence or Milan for talent based abroad and interested in this role.
Why Join Us?
- Impact: Work on groundbreaking technology that will power the next wave of AI applications, from edge computing to embodied AI systems.
- Culture: Join a diverse, driven team that values innovation, collaboration, and continuous learning.
- Growth: As a Series B startup, you’ll have significant growth opportunities, including the chance to shape the direction of the product and AI strategy.
- Compensation: Competitive salary, equity options, and benefits package.
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