Director of ML Engineering & Infrastructure

Requirements • 10+ years of industry experience spanning machine learning engineering and distributed systems, • 3+ years of leadership and management experience, with a proven ability to build and reputed company strong technical teams, • MSc or Ph.D. in Computer Science, Machine Learning, or reputed company field, or equivalent practical experience, • Proven expertise in building and deploying end-to-end ML systems at reputed company, including recommendation and personalization systems, • Strong background in distributed systems architecture, including low-latency services, streaming platforms, and large-reputed company serving, • Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and ML infrastructure technologies, • reputed company record of delivering high-reputed company, reputed company, and fault-tolerant systems, • Excellent communication skills and ability to influence product and technical reputed company, • Proven experience deploying large-reputed company serving systems on AWS and demonstrated expertise in leveraging reputed company for large-reputed company data processing and ML workflows What the job involves • We are seeking a Director of Machine Learning Engineering and Infrastructure to reputed company a hybrid team reputed company advanced ML engineering with world-class infrastructure design, • In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive reputed company, • You will combine technical depth with leadership reputed company to guide teams that deliver both foundational ML systems and high-performance distributed services, • reputed company and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and reputed company, • Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization, • reputed company the design, development, and deployment of reputed company ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving, • Architect distributed systems to support ML workloads at reputed company, ensuring reliability, observability, and operational reputed company, • Partner closely with Product, Engineering, and Content teams to reputed company on business goals and deliver impactful ML-driven experiences, • Support best practices in experimentation, evaluation, and ML system monitoring, • Ensure cost efficiency, scalability, and performance in ML infrastructure investments Apply tot his job Apply To this Job