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Strong employer brand but senior, specialized ML/AI role reduces broad applicant density.
Requires deep ML/AI architecture and domain-specific communications experience, limiting cross-industry transferability.
Explicit 10+ years, leadership plus deep ML/MLOps and cloud architecture requirements create stringent screening.
Lead and manage a high-performing engineering team specializing in AI/ML for unified communication products, ensuring delivery of AI-driven features on time and at high quality.
Define and execute the technical strategy, architecture, and roadmap for AI/ML integration across products, overseeing all stages from model training to MLOps and production monitoring.
Collaborate cross-functionally with product, AI research, data governance, and legal teams to align AI initiatives with business goals and compliance requirements.
Minimum 10 years in software engineering with at least 3 years in technical leadership or management overseeing AI/ML or data-intensive teams.
Deep hands-on experience with full AI/ML lifecycle including model building, deployment, and MLOps.
Strong programming skills in Python and Java/C++ and familiarity with ML frameworks like TensorFlow, PyTorch, Scikit-learn.
Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or related technical field.
Experienced leader capable of managing mixed teams of software engineers, ML engineers, and data scientists in an enterprise setting with complex AI/ML integration.
Proven ability to architect and deliver scalable cloud-native AI solutions on platforms like AWS, Azure, or GCP.
Strategic thinker who can drive technology innovation and communicate complex AI/ML concepts effectively to technical and non-technical stakeholders.