This position is needed to scope, design, and deploy machine learning systems into the real world. The individual will closely partner with Product & Engineering teams to execute the roadmap for Twilio's AI/ML products and services.

You will understand customers' needs, build data products that work at a global scale, and own end-to-end execution of large-scale ML solutions.

To thrive in this role, you must have a deep background in ML engineering and a consistent track record of solving data & machine-learning problems at scale.

Responsibilities:

• Build and maintain scalable machine learning solutions in production
• Train and validate both deep learning-based and statistical-based models considering use-case, complexity, performance, and robustness
• Demonstrate end-to-end understanding of applications and develop a deep understanding of the 'why' behind our models & systems
• Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements, and define the scope of the systems needed
• Work closely with data platform teams to build robust scalable batch and real-time data pipelines
• Collaborate with software engineers, build tools to enhance productivity, and to ship and maintain ML models
• Drive high engineering standards on the team through mentoring and knowledge sharing
• Uphold engineering best practices around code reviews, automated testing, and monitoring

Qualifications:

• 7+ years of applied ML experience with proficiency in Python
• Strong background in the foundations of Machine Learning and building blocks of modern Deep Learning
• Track record of building, shipping, and maintaining Machine Learning models in production in an ambiguous and fast-paced environment
• Track record of designing and architecting large-scale experiments and analysis to inform product roadmap
• Familiarity with ML Ops concepts related to testing and maintaining models in production such as testing, retraining, and monitoring
• Demonstrated ability to ramp up, understand, and operate effectively in new application/business domains
• Experience working in an agile team environment with changing priorities
• Experience of working on AWS

Desired:

• Experience with Large Language Models

Travel:

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

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