Machine Learning Engineer
Posted on 3/26/2024

5,001-10,000 employees

Customer engagement platform & developer of communications APIs
Company Overview
Twilio's mission is to fuel the future of communications. By making communications a part of every software developer's toolkit, Twilio is enabling innovators across every industry to reinvent how companies engage with their customers.
Data & Analytics

Company Stage


Total Funding





San Francisco, California

Growth & Insights

6 month growth


1 year growth


2 year growth

Remote in USA
Experience Level
Desired Skills
Python NLTK
Data Structures & Algorithms
Natural Language Processing (NLP)
AI & Machine Learning
Applied Machine Learning
Deep Learning
  • 3+ years of applied ML experience
  • Strong background in the foundations of machine learning and building blocks of modern deep learning.
  • Proficiency in Python or Java and familiarity with design patterns.
  • Track record of building, shipping and maintaining machine learning models in production.
  • Extensive experience in technologies such as PyTorch, Tensorflow, Scikit-learn, Spacy, NLTK, application frameworks (e.g., Flask)
  • Deep understanding of ML model implementation cycle (e.g., feature engineering, training/serving, A/B test, model selection, etc.), algorithms (e.g., xgboost, time series models, deep learning, graph neural networks, optimization) and domains (e.g., forecasting, personalization and recommendation system, NLP, embedding representation)
  • Familiarity with MLOps concepts related and maintaining models in production such as testing, versioning, model registry, retraining, and monitoring.
  • Demonstrated ability to ramp up, understand, and operate effectively in new application / business domains.
  • Good written and verbal communication skills - You are confident in writing down and presenting your designs and decisions throughout the development lifecycle. You are also comfortable providing and receiving feedback in an Agile environment.
  • Build and maintain scalable, high quality machine learning solutions in production
  • Design and implement tools and procedures to evaluate performance and accuracy of models and data.
  • Work closely with software engineers, build tools to enhance productivity and to ship and maintain ML models
  • Demonstrate end-to-end understanding of applications and “why” behind models & systems and develop high quality ML-based software at scale
  • Truly own the product you work on. Be responsible for SLA, on call, incident resolution, customer feedback, and participate in blameless post-mortems to make our products better.
  • Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems and leverage state-of-the-art Statistics, Machine Learning, Deep Learning and Gen AI to address the business problems.
  • Drive high engineering standards on the team through code review, automated testing, and mentoring.
  • Collaborate and brainstorm product ideas with product managers, designers, and engineers.