Staff, Machine Learning Engineer (L4)

See yourself at Twilio

Join the team as Twilio's next Staff, Machine Learning Engineer in our Identity Resolution team.

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, diverse team 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.

About the job

Twilio is a leader in providing innovative solutions to complex data challenges, helping businesses better understand their customers. Twilio is at the forefront of transforming how businesses understand and engage with their customers. Leveraging advanced identity resolution technologies, we unify and enrich disparate data sources to create comprehensive customer profiles.

As a Staff Engineer specializing in Machine Learning and Feature Engineering for the Identity Resolution team, you will drive the development of sophisticated ML models and advanced feature engineering techniques designed to enhance our identity resolution capabilities. Your work will play a critical role in improving our systems' ability to match and unify customer identities accurately, enabling more personalized customer experiences and strategic business insights. Your role will also involve building robust data infrastructure to support and scale our machine learning initiatives.

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

Responsibilities

In this role, you'll:

• Design, implement, and refine machine learning models that improve the precision and recall of identity resolution algorithms.
• Develop and optimize feature engineering methodologies to extract meaningful patterns from large and complex datasets that enhance identity matching and unification.
• Develop and maintain scalable data infrastructure to support the deployment and training of machine learning models, ensuring that they run efficiently under varying loads.
• 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
• Ensure high standards of operational excellence by implementing efficient processes, monitoring system performance, and proactively addressing potential issues.
• Drive engineering best practices around code reviews, automated testing and monitoring

Qualifications

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!

• Required:

• 7+ years of applied ML experience.
• Proficiency in Python, Java or Golang is preferred.
• Extensive experience in feature engineering and developing data-driven frameworks that enhance identity matching algorithms.
• Strong background in the foundations of machine learning and building blocks of modern deep learning
• Deep understanding of machine learning frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with big data technologies like Apache Spark or Hadoop, and familiarity with cloud platforms (AWS, Azure, Google Cloud) for scalable data processing.
• Familiarity with ML Ops concepts related to testing and maintaining models in production such as testing, retraining, and monitoring.
• Experienced with 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:

• Exposure to Advertising Technology, Marketing Technology domains.
• Experience designing and implementing highly available, performant, and fault-tolerant distributed systems that provide durable and (eventually) consistent results.
• Experience with Large Language Models

Location

This role will be remote and based in our Bengaluru, India office.

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

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 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.