Staff Machine Learning Engineer (L4)
See yourself at Twilio
Join the team as Twilio’s next Staff Machine Learning Engineer.
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.
You will understand customers need, build data products that works at a global scale and 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 organizations.
Responsibilities
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
Collaborate 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
Uphold engineering best practices around code reviews, automated testing and monitoring
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:
7+ years of applied ML experience with proficiency in Python
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
Desired:
Experience with Large Language Models
Location
This role will be remote, and based in India
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.
About the job
Apply for this position
Staff Machine Learning Engineer (L4)
See yourself at Twilio
Join the team as Twilio’s next Staff Machine Learning Engineer.
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.
You will understand customers need, build data products that works at a global scale and 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 organizations.
Responsibilities
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
Collaborate 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
Uphold engineering best practices around code reviews, automated testing and monitoring
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:
7+ years of applied ML experience with proficiency in Python
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
Desired:
Experience with Large Language Models
Location
This role will be remote, and based in India
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.