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Metro location, broad AI skillset, and a generalist AI Engineer title increase candidate competition.
Core ML skills are transferable, but AR/VR and production-deployment needs increase domain specificity.
Requires specialized ML research and production deployment skills though lacks explicit years requirement.
Lead research, prototyping, and implementation of advanced AI techniques such as generative models, transformers, and reinforcement learning across mixed reality applications.
Build, train, deploy, and optimize AI/ML models and scalable systems with low latency and high availability for immersive interactive media.
Collaborate cross-functionally with designers, product managers, and AR/VR/MR developers to integrate AI solutions into extended reality experiences.
Proficiency in at least one AI-related programming language (e.g., Python) and AI frameworks like TensorFlow or PyTorch.
Experience with AI techniques including generative models, large language models, computer vision, or reinforcement learning.
Strong problem-solving skills with ability to rapidly learn new tools and frameworks independently.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in applying cutting-edge AI research in product contexts, particularly in generative AI and spatial computing domains.
Comfortable working autonomously with minimal supervision and driving innovation with experimental AI projects.
Able to architect and optimize AI model deployment pipelines balancing performance, cost, and scalability in production environments.