Machine Learning Engineer

<h3>📋 Description</h3> • This position is needed to scope, design, and deploy machine learning systems into the real world, the individual will closely partner with Product &amp; Engineering teams to execute the roadmap for Twilio’s AI/ML products and services. • You will understand customers need, build data products that works 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 &amp; machine-learning problems at scale. You are a self-starter, embody a growth attitude, and collaborate effectively across organization. • 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 &amp; 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 realtime 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. <h3>🎯 Requirements</h3> • 7.5+ 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. • You have a clear understanding of frameworks like - PyTorch, TensorFlow, or Keras, why and how these frameworks do what they do • 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. • You’ve explored modern data storage, messaging, and processing tools (Kafka, Apache Spark, Hadoop, Presto, DynamoDB etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar • Experience working in an agile team environment with changing priorities • Experience of working on AWS. <h3>🏖️ Benefits</h3> • competitive pay • generous time off • ample parental and wellness leave • healthcare • a retirement savings program • much more