Machine Learning Engineer

See yourself at Twilio

Join the team as Twilio’s next Machine Learning Engineer.

About the job

This position is needed to drive innovation and the development of cutting-edge products that serve developers, builders, and operators within Twilio’s Data & Observability Substrate organization.

This is a hands-on, builder-focused engineering role that bridges Product, Design, and Engineering to develop, evaluate, and maintain scalable, low-latency, ML-based systems for real-time applications. You will lead rapid research-to-production cycles that translate business ideas into solutions for complex problems—such as streaming anomaly detection, recommendation systems, predictive modeling, and agentic AI frameworks—with the goal of delivering personalized customer experiences.

You will collaborate closely with a cross-functional team of engineers, architects, product managers, UI/UX designers, and ML/data science partners to deliver robust, reliable solutions that power customer success.

Responsibilities

In this role, you’ll:

• Partner with product, UX, and technical stakeholders to analyze business problems, clarify requirements, define scope, and translate them into measurable ML problem statements.
• Design, implement, and maintain scalable, enterprise-grade ML solutions in production.
• Build reproducible ML workflows for data preparation, training, evaluation, and inference using modern orchestration and MLOps tooling.
• Implement monitoring and evaluation frameworks to continuously improve data quality, model performance, latency, and cost through feedback loops.
• Partner cross-functionally with Product, Data Science/ML, Engineering, and Security to deliver resilient, scalable, and compliant ML-powered services.
• Demonstrate end-to-end systems understanding and articulate the “why” behind model and system design choices.
• Own operational excellence: SLAs, on-call, incident response, customer feedback triage, and blameless post-mortems.
• Drive engineering excellence via AI-assisted SDLC, code reviews, automated testing, MLOps best practices, knowledge-sharing, and mentoring.
• Actively adopt AI-assisted practices to improve implementation and collaboration efficiency.

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

• Strong foundation in ML/AI (statistics, probability, optimization) with the ability to apply these concepts to real-world problems.
• 5+ years of experience building, deploying, and operating data and ML systems in production.
• Proficient in Python, Java, and SQL; strong software engineering fundamentals (system design, testing, version control, code reviews).
• Hands-on experience with workflow orchestration and data pipelines (e.g., Airflow, Kubeflow) and cloud data platforms/storage (e.g., SageMaker Feature Store, Snowflake, DynamoDB, OpenSearch).
• Experience with the ML lifecycle and MLOps tooling (e.g., MLflow, Metaflow, SageMaker; LLM/agent frameworks such as LangChain/LangGraph; model evaluation/observability tools such as Galileo or similar).
• Working knowledge of containerization and cloud infrastructure, including Docker and Kubernetes, GitOps/CI/CD tools (e.g., Argo CD), and at least one major cloud platform (AWS, GCP, or Azure).
• Understanding of data modeling and scalable systems, including distributed computing and streaming frameworks (e.g., Spark/EMR, Flink, Kafka Streams); familiarity with GPU-based implementation is a plus.
• Demonstrated ability to ramp up quickly and operate effectively in new application/business domains.
• Strong written and verbal communication skills: able to document and present designs and decisions, and comfortable giving/receiving feedback in an Agile environment.

Desired

• Familiarity with ML problem areas and techniques, including recommendation systems (e.g., graph-based approaches, two-tower models), time-series modeling (classical and deep learning), representation learning (e.g., embeddings), anomaly detection, and causal inference.
• Practical experience with LLMs and generative AI workflows, including foundation model fine-tuning, RAG, and vector databases.
• Evidence of technical leadership/impact, such as contributions to open-source data/ML projects and/or published technical presentations, blog posts, papers, or research.
• Domain experience (plus) in communications, marketing automation, or customer engagement analytics.
• Familiarity with AI-assisted development tools (e.g., Claude, GitHub Copilot/Codex, Cursor, etc.).
• Advanced degree preferred (M.S. or Ph.D.) in a relevant field.

Location

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

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.

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. : $155,520.00 - $194,400.00. 
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $164,640.00 - $205,800.00.
• Based in the San Francisco Bay area, California: $182,960.00 - $228,700.00
• This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

Application deadline information

Applications for this role are intended to be accepted until April 20th, but may change based on business needs.