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Staff Machine Learning Engineer

Build and maintain scalable machine learning solutions in production.
Bengaluru, Karnataka, India
8 months ago
Segment (Acquired by Twilio)

Segment (Acquired by Twilio)

Software and APIs to collect, clean, and control customer data.

7 Similar Jobs at Segment (Acquired by Twilio)

✨ About The Role

See yourself at Twilio

Join the team as our next Staff, Machine Learning Engineer in our Comms Platform Engineering team

Who we are & why we’re hiring

Twilio powers real-time business communications and data solutions that help companies and developers worldwide build better applications and customer experiences.

Although we're headquartered in San Francisco, we have presence throughout South America, Europe, Asia and Australia. We're on a journey to becoming a global company that actively opposes racism and all forms of oppression and bias. At Twilio, we support diversity, equity & inclusion wherever we do business.

About the job

This position is needed to scope, design, and deploy machine learning systems into the real world, the individual will closely partner with Product & Engineering teams to execute the roadmap for Twilio’s AI/ML products and services.

Twilio is looking for a Staff Machine Learning engineer to join the rapidly growing Comms Platform Engineering team of our Messaging business unit. You will understand the needs of our customers and build data products that solve their needs at a global scale. Working side by side with other engineering teams and product counterparts, you will 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 & machine-learning problems at scale. You are a self-starter, embody a growth attitude, and collaborate effectively across the entire Twilio organization


In this role, you’ll:

  • 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 & 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
  • Work closely 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
  • Drive engineering best practices around code reviews, automated testing and monitoring


Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also 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!


  • 7+ years of applied ML experience.
  • Proficiency in Python is preferred. We will also consider strong quantitative candidates with a background in other programming languages
  • 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


  • Experience with Large Language Models


This role will be based in our Bengaluru, India office. Approximately 10% travel is anticipated.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Twilio is proud to be an equal opportunity employer. Twilio is proud to be an Equal Employment Opportunity and Affirmative Action 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. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Twilio is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at .

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Staff Machine Learning Engineer
Bengaluru, Karnataka, India
About Segment (Acquired by Twilio)
Software and APIs to collect, clean, and control customer data.