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Optimize and benchmark deep learning training and inference stacks on HPC/GPU hardware; profile and triage system bottlenecks; build automation tools; develop kernels and systems for new models; lead design reviews, review code, document work, and represent the lab at conferences.

Lead research to improve LLM efficiency and architectures, design and implement NLP algorithms (using PyTorch), integrate LLMs with vision models, optimize models and data pipelines, collaborate on code/design reviews, publish technical reports and papers, represent the institute at conferences, and contribute to ML infrastructure and model evaluation.

Design, build, and maintain scalable ML infrastructure for training and inference of LLM, TTS, and multimodal systems. Own model lifecycle, Kubernetes-based deployments (EKS/Helm), CI/CD, monitoring, cost optimization, infra-as-code (Terraform), and collaborate with researchers to productionize models and observability pipelines.

Design, extend, and maintain distributed training infrastructure: modify frameworks (DeepSpeed, FSDP, etc.), implement distributed optimizers, build multi-node launch/config systems, implement experiment tracking and monitoring, optimize reliability and performance, and write production-quality ML infra code in PyTorch or JAX.

Develop and maintain backend services (Python/FastAPI), data pipelines, and RESTful APIs; build frontend web apps (Vue/React/Next) and Flutter mobile apps; integrate model inference and data visualization; manage PostgreSQL databases; implement CI/CD, Docker, and cloud deployment; ensure performance, security, and cross-team collaboration.

Coordinate cross-functional work across research, engineering, product, marketing, and community for the Abu Dhabi lab. Translate priorities into project plans, track roadmaps and readiness milestones, run end-to-end model launches, liaise with MarComms and partners, maintain lightweight processes, report progress and risks to leadership, and drive resolution of blockers while improving launch and delivery processes.

Lead day-to-day IT operations across U.S. and UAE offices, ensure infrastructure uptime, manage endpoints and MDM, enforce security and compliance, support employee onboarding and high-touch IT service, manage assets and vendors, and coordinate global IT standards and projects to enable scalable, reliable technology operations.

Lead research and engineering for data-centric LLM development: collect and curate web-scale datasets, build pipelines and tooling for fine-tuning, retrieval, RAG, and reasoning systems, prototype APIs and infrastructure, evaluate model performance, publish findings, and collaborate across research and engineering teams.

Manage end-to-end HPC infrastructure projects for large-scale GPU clusters: coordinate vendors and internal stakeholders, track milestones and risks, maintain documentation and governance, support compliance and export-control tracking, and produce executive reports and dashboards to ensure research timelines are met.

Support the Paris IFM lab with day-to-day finance and administrative operations: payroll processing, budget monitoring, procurement, vendor relations, IT coordination, compliance with MBZUAI and French regulations, recordkeeping, travel coordination, and event support to enable researchers to focus on scientific work.