Senior Machine Learning Engineer

Today, Twilio powers the delivery of billions of the world’s communications. Increasingly, we’re hearing from our B2C customers that they’re struggling to harness the massive amounts of valuable data they generate, much of which stems from the communications we help them send. We seek to uncover how Twilio can help customers utilize their valuable data to create unique, individualized experiences that their competitors can’t replicate. We want to help them become more proactive (outcome-driven) than reactive (event-driven) in their customer engagements. We are a new initiative and team at Twilio that will function much like an internal start-up. If you want to shape the future of B2C Customer Engagement and Twilio, this project is for you!

Twilio is a company that is empowering the world’s developers with modern communication in order to build better applications. Twilio is truly unique; we are a company committed to your growth, your learning, your development, and your entire employee experience. We only win when our employees succeed and we’re dedicated to helping you develop your strengths. We have a cultural foundation built on diversity, inclusion, and innovation and we want you and your ideas to thrive at Twilio.

Responsibilities

EMPOWER OTHERS: Be part of a small, high-impact and multi-talented engineering team. Show strong engagement in the team setting
WEAR THE CUSTOMER’S SHOES: Passion for and demonstrated track record of executing product opportunities deeply grounded in customer needs
DRAW THE OWL: Self-starter who can see the big picture and prioritize work to make the largest impact
BE BOLD: Help us take one of the world’s most extensive communication data sets and transform it into cutting-edge AI applications and products that solve meaningful customer problems
BE INCLUSIVE: Collaborating and brainstorming product ideas with product managers, other data scientists and engineers
DON’T SETTLE: Experienced working at a massive scale with distributed, scalable systems, including making tradeoffs for consistency/availability
NO SHENANIGANS: Experience successfully applying data science and machine learning to real-world problems

Requirements

Personal traits: Curious, humble, team player
Professionally: Passionate, customer-obsessed, gets things done, highly collaborative, excellent communicator, and very comfortable with rapid change and uncertainty
You have hands on experience developing, deploying and monitoring a large scale machine learning model in production
Ph.D. or MS in Computer Science, Data Science, Statistics, or related field
7+ years of applied ML experience in statistical and mathematical modeling such as supervised and unsupervised machine learning, deep learning, and/or reinforcement learning
You are familiar with concepts related to testing and maintaining models in production such as A/B testing, retraining, monitoring model performance
You’ve explored modern data storage, messaging, and processing tools (Kafka, Spark, Hadoop, Cassandra, etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar
You have a deep understanding of frameworks like – PyTorch, TensorFlow, or Keras, why and how these frameworks do what they do
Proficiency in Python is preferred. We will also consider strong quantitative candidates with a background in other programming languages
Experience working in an agile team environment
Big plus: Experience in AWS cloud computing