Deep Learning Architect, AWS AI Innovation Hub

Job Description: Deep Learning Architect

Are you ready to architect the foundational models that will define the next decade of industry? The AWS Generative AI Innovation Center is seeking a Deep Learning Architect to join our elite cross-functional team in Dubai.

In this role, you aren’t just building “features”—you are designing the high-performance blueprints for enterprise-scale Generative AI. You will act as the bridge between raw research and production-grade implementation, collaborating with global technology and business teams to solve the most complex challenges for AWS customers. From optimizing massive transformer architectures to designing efficient multi-modal pipelines on Annapurna Labs silicon (Trainium/Inferentia), you will be at the absolute frontier of cloud-based AI.

Your Technical & Strategic Mission

Foundational Model Architecture

• Generative System Design: Lead the architectural design of large-scale generative models (LLMs, Diffusion, etc.), ensuring they are optimized for cost, latency, and throughput.

• Algorithm Innovation: Research and implement advanced techniques such as Sparse Attention, Mixture of Experts (MoE), and Quantization to push the boundaries of model performance.

• Multi-Modal Integration: Design systems that seamlessly integrate text, image, audio, and video modalities into unified, context-aware customer solutions.

Scalable Infrastructure & Deployment

• Distributed Training: Architect training pipelines for massive datasets across distributed GPU/TPU clusters, utilizing frameworks like PyTorch, JAX, and DeepSpeed.

• Cloud-Native AI: Leverage the full power of the AWS stack (SageMaker, Bedrock, and EC2 UltraClusters) to build “self-healing” and auto-scaling AI services.

• Hardware Optimization: Partner with internal teams to optimize model performance specifically for AWS Trainium and Inferentia chips.

Customer-Centric Innovation

• Consultative Architecture: Work directly with strategic AWS customers to translate high-level business goals into rigorous deep learning architectures.

• Cross-Functional Leadership: Mentor a multidisciplinary team of applied scientists and software engineers, fostering a culture of technical excellence and “customer obsession.”

What You Bring to the Innovation Center

• Experience: Extensive experience in deep learning research and production-scale model architecture.

• Technical Mastery: Expert proficiency in Python and deep learning frameworks (PyTorch or JAX).

• Distributed Computing: Proven track record of training and deploying models at the “billion-parameter” scale.

• Cloud Expertise: Deep knowledge of cloud infrastructure, specifically AWS services (SageMaker, Lambda, ECS).

• Communication: The ability to explain complex architectural trade-offs to C-suite executives and PhD researchers alike.

Job Overview Data