Principal Machine Learning & Data Engineer

Twilio; Canada; Remote; CAD 257,000 - 341,000; Full time

Job summary

A leading communications platform is seeking a Principal Machine Learning & Data Engineer to design and operate their internal ML-and-data platform. The role involves architecting cloud-native pipelines and ensures best practices in data processing. Ideal candidates will have over 7 years of experience, expertise in Python and cloud technologies, and strong project leadership abilities. This position includes competitive compensation and a remote work environment.

Benefits

Competitive pay

Generous time off

Healthcare benefits

Retirement savings program

Qualifications

• 7+ years building and operating production data or machine-learning systems at scale.
• Hands-on mastery of distributed data frameworks and streaming platforms.
• Proven ability to lead technical projects end-to-end.

Responsibilities

• Architect and evolve Twilio’s end-to-end ML and real-time data platforms.
• Implement MLOps best practices for hundreds of daily deployments.
• Mentor staff and senior engineers.

Skills

Python

Java

Distributed data frameworks (Spark/Flink)

Kubernetes/EKS

MLOps tooling (MLflow, Kubeflow)

SQL/NoSQL

Education

Bachelor's or higher in Computer Science, Engineering, Mathematics

Tools

Terraform

Docker

Job description

Principal Machine Learning & Data Engineer

Remote - US

Who we are

At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.

Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.

See yourself at Twilio

Join the team as Twilio’s next L5 Machine Learning & Data Engineer to lead the design, build, and operation of the internal ML-and-data platform that powers every customer interaction. You will architect cloud-native pipelines, model-serving infrastructure, and developer tooling that allow Twilio’s product teams to iterate rapidly and safely at scale, advancing our mission to unlock the imagination of builders.

About the job

Twilio’s next L5 Machine Learning & Data Engineer to lead the design, build, and operation of the internal ML-and-data platform that powers every customer interaction. You will architect cloud-native pipelines, model-serving infrastructure, and developer tooling that allow Twilio’s product teams to iterate rapidly and safely at scale, advancing our mission to unlock the imagination of builders.

Responsibilities

In this role, you’ll:

• Architect and evolve Twilio’s end-to-end ML and real-time data platforms for reliability, security, and cost efficiency.
• Design scalable feature stores, streaming and batch pipelines, and low-latency model-serving layers on AWS.
• Implement MLOps best practices—automated testing, CI/CD, monitoring, and rollback—for hundreds of daily deployments.
• Own system design reviews, threat modeling, and performance tuning for high-volume communications workloads.
• Lead cross-functional engineering efforts, breaking down complex initiatives into executable roadmaps.
• Mentor staff and senior engineers, raising the technical bar through code reviews and pair programming.
• Partner with Product, Security, and Compliance to meet stringent privacy and governance requirements (HIPAA, SOC 2, GDPR).
• Champion a culture of experimentation, data-driven decision-making, and continuous improvement.

Qualifications

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Bachelor’s or higher in Computer Science, Engineering, Mathematics, or equivalent practical experience.
• 7+ years building and operating production data or machine-learning systems at scale.
• Expert fluency in Python and one compiled language (Java, Scala, Go, or C++).
• Hands-on mastery of distributed data frameworks (Spark/Flink), SQL/NoSQL stores, and streaming platforms (Kafka/Kinesis).
• Demonstrated success designing cloud-native architectures on AWS, including Terraform-managed infrastructure.
• Deep knowledge of container orchestration (Kubernetes/EKS), service-mesh networking, and autoscaling strategies.
• Practical experience implementing MLOps tooling such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Strong grasp of model-lifecycle concerns—feature engineering, offline/online parity, A/B testing, drift detection, and retraining.
• Proven ability to lead technical projects end-to-end and influence without authority across multiple teams.
• Exceptional written and verbal communication skills, with a bias toward clarity and action.

Location

This role will be remote, but is not eligible to be hired in CA, CT, NJ, NY, PA, WA.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Compensation

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C.: $184,500 - $230,700.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $195,300 - $244,200.
• Based in the San Francisco Bay area, California: $217,000 - $271,300.

Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.