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Staff Machine Learning Engineer (L4)Twilio • Saint Paul, Illinois, United States
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Staff Machine Learning Engineer (L4)

Twilio
  • US
    Saint Paul, Illinois, United States
  • US
    Saint Paul, Illinois, United States
Jetzt Bewerben

Über

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. We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
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
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
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.
Twilio thinks big. Do you?
We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts.
So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions.
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. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.
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  • Saint Paul, Illinois, United States

Sprachkenntnisse

  • English
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