Architect and design end-to-end AI/ML solutions for the MediaOS platform
Define and implement scalable ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
Lead the design of cloud-native, distributed AI systems leveraging modern frameworks and high-performance computing environments
Partner with product, data engineering, and platform teams to translate business requirements into robust AI-driven solutions
Establish and enforce MLOps best practices, including CI/CD, model versioning, observability, governance, and lifecycle management
Evaluate and integrate emerging AI technologies, including Generative AI, LLMs, and NLP applications where applicable
Drive data strategy alignment, ensuring high-quality, well-governed datasets to support model development and scalability
Mentor and guide engineers and data scientists, fostering a culture of innovation, collaboration, and technical excellence
Architect secure AI platforms, including authentication and authorization models (e.g., RBAC, ABAC)

8+ years of experience in AI/ML, Data Science, or related fields
Proven track record of designing and deploying production-grade ML systems at scale
Strong programming expertise in Python (preferred) and/or Java/Scala
Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn
Deep understanding of data architecture, distributed systems, and cloud platforms (AWS, Azure, or GCP)
Experience with real-time and batch processing systems
Strong knowledge of MLOps tools, frameworks, and lifecycle practices
Experience designing secure AI systems, including authentication and authorization frameworks (RBAC, ABAC)

AI/ML Architect, MediaOS Platform

Key skills