Architect, Machine Learning

Summary

Join Twilio as an AI and Machine Learning Architect to provide technical leadership and architectural guidance to the India-based AI/ML team. This role involves crafting and executing a comprehensive machine learning strategy, designing scalable ML systems, collaborating with cross-functional teams, driving innovation, overseeing the ML model lifecycle, mentoring junior team members, and ensuring model reliability. The position requires charting the future of Twilio’s global machine learning teams and infrastructure, serving as a knowledge center for company-wide teams, and having exposure to various ongoing projects. The successful candidate will be responsible for the technical leadership and architectural guidance of the AI/ML team. This is a remote position based in India.

Requirements

• Earn a Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field
• Have minimum of 7 years in machine learning, with at least 3 years in a leadership or architect role
• Possess strong skills in Python, and experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn
• Demonstrate a deep understanding of cloud platforms such as AWS, GCP, or Azure, especially in deploying and scaling ML models
• Show proficiency in the design and implementation of ML supporting infrastructure for training, serving, and monitoring applications
• Possess proven ability to solve complex problems and develop data-driven solutions
• Have excellent verbal and written communication skills to articulate complex concepts to diverse audiences
• Demonstrate experience working collaboratively within a dynamic, fast-paced environment

Responsibilities

• Develop ML strategy: Craft and execute a comprehensive strategy for machine learning initiatives that align with Twilio’s overall objectives
• Lead architecture and design: Lead the design of scalable, efficient ML systems that integrate seamlessly with Twilio’s communication platform
• Collaborate cross-functionally: Partner with teams across data engineering, software development, and product management to incorporate ML models into existing services
• Drive innovation and leadership: Drive innovation by exploring new technologies and methodologies, setting best practices for the company
• Manage model lifecycle: Oversee the end-to-end lifecycle of ML models, including development, deployment, monitoring, and refinement
• Mentor and train: Provide guidance and mentorship to junior team members, fostering a culture of learning and growth
• Ensure quality assurance: Ensure the reliability and accuracy of ML models through rigorous testing and validation processes

Preferred Qualifications

• Earn an advanced degree (Ph.D.) in a relevant field
• Have experience in the telecommunications sector or related fields
• Showcase publications or research contributions in the field of machine learning or data science
• Demonstrate experience with additional tools such as Docker, Kubernetes, and data processing frameworks like Apache Spark
• Possess the ability to quickly learn new technologies and apply them effectively
• Have the capacity to anticipate industry trends and contribute to strategic planning

Benefits

Remote work