Architect and oversee the adoption of scalable AI infrastructures and select appropriate frameworks, tools, and technologies.
Ensure all products and systems adhere to a commonly defined performance evaluation methodology and appropriate monitoring and reporting systems are in place.
Ensure AI solutions adhere to ethical standards and regulatory requirements.
Collaborate with data scientists, engineers, and business stakeholders to integrate AI into products and services.
Provide technical guidance and mentorship to cross-functional teams.
Requirements
Strong knowledge of Machine Learning, Deep Learning
Generative AI & LLM Integration
Edge AI & Real-time Inference
Proficiency in Python, and ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers
Experience with cloud platforms (Azure, GCP)
Understanding of data architecture, big data technologies, and model deployment
Strong understanding of ML training pipelines, data lifecycle, and model serving concepts
Experience with GPU orchestration (e.g., NVIDIA GPU Operator, MIG).
Experience with MLOps and AI governance frameworks
Familiarity with ethical AI practices and data privacy regulations
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