Engineering Manager - Machine Learning

As the Machine Learning Engineering Manager, your primary responsibility is to lead the data science, machine learning, and related activities within the company. You will collaborate closely with engineers and machine learning specialists to explore innovative ways to leverage emerging technologies for enhancing business processes and delivering increased value to customers. **Key Responsibilities:** - Build and oversee a team comprising data engineering, MLOps engineers, and machine learning engineers - Lead the team in designing an AI Engineering platform to facilitate the deployment and scalability of machine learning models - Develop tools and capabilities for tasks ranging from data ingestion to feature engineering, data management, and organization - Create tools and capabilities for distributed optimization - Collaborate with stakeholders from the research and software engineering departments to provide support and align efforts - Develop tools and capabilities for model management and monitoring model performance - Guide the team in operating services at internet scale with high availability and reliability - Propose and implement engineering and research best practices for scaling ML-powered features, enabling fast iteration and efficient experimentation with novel features - Contribute to and influence the ML infrastructure roadmap based on feedback from internal customers **Qualifications Required:** - Preferred Ph.D. or Master's degree in machine learning, artificial intelligence, software engineering, or a related field - 8+ years of experience in machine learning - Minimum 2 years of experience in a leadership role - Comprehensive understanding of the machine learning pipeline from data ingestion to production - Proficiency in machine learning operations, software engineering, and architecture - Experience with large-scale systems, including parallel computing - Prior experience in architecting and developing an AI platform to support the productionization of ML models - Familiarity with MLOps systems - Strong programming skills in Python or similar scientific computing languages - Proficiency in frameworks for machine learning and data science such as scikit-learn, pandas, NumPy - Hands-on experience with ML tools like TensorFlow, Keras, and PyTorch - Ability to translate successful research ideas from experimentation to production - Excellent written and oral communication skills, with the ability to drive cross-functional requirements with product and engineering teams In summary, as the Machine Learning Engineering Manager, your role involves leading a team to develop and deploy cutting-edge machine learning solutions while collaborating with various stakeholders to drive business value through innovative technology applications. As the Machine Learning Engineering Manager, your primary responsibility is to lead the data science, machine learning, and related activities within the company. You will collaborate closely with engineers and machine learning specialists to explore innovative ways to leverage emerging technologies for enhancing business processes and delivering increased value to customers. **Key Responsibilities:** - Build and oversee a team comprising data engineering, MLOps engineers, and machine learning engineers - Lead the team in designing an AI Engineering platform to facilitate the deployment and scalability of machine learning models - Develop tools and capabilities for tasks ranging from data ingestion to feature engineering, data management, and organization - Create tools and capabilities for distributed optimization - Collaborate with stakeholders from the research and software engineering departments to provide support and align efforts - Develop tools and capabilities for model management and monitoring model performance - Guide the team in operating services at internet scale with high availability and reliability - Propose and implement engineering and research best practices for scaling ML-powered features, enabling fast iteration and efficient experimentation with novel features - Contribute to and influence the ML infrastructure roadmap based on feedback from internal customers **Qualifications Required:** - Preferred Ph.D. or Master's degree in machine learning, artificial intelligence, software engineering, or a related field - 8+ years of experience in machine learning - Minimum 2 years of experience in a leadership role - Comprehensive understanding of the machine learning pipeline from data ingestion to production - Proficiency in machine learning operations, software engineering, and architecture - Experience with large-scale systems, including parallel computing - Prior experience in architecting and developing an AI platform to support the productionization of ML models - Familiarity with MLOps systems - Strong programming skills in Python or similar scientific computing languages - Proficiency in frameworks for machine learning and data scienc