Machine Learning Engineer, AccSec

Bengaluru, Karnataka, India

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Twilio

Connect with customers on their preferred channels—anywhere in the world. Quickly integrate powerful communication APIs to start building solutions for SMS and WhatsApp messaging, voice, video, and email.

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Machine Learning Engineer

at Twilio (View all jobs)

Bengaluru, Karnataka, India

See yourself at Twilio

Join the team as our next MACHINE LEARNING ENGINEER

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're on a journey to becoming a globally antiracist company that supports diversity, equity & inclusion wherever we do business. We employ thousands of Twilions worldwide, and we're looking for more builders, creators, and visionaries to help fuel our growth momentum.

About the job

This position is needed to scope, design, and deploy machine learning systems into the real world to ensure that communication across Twilio platforms remains legal, safe and wanted. 

As a Machine-Learning Engineer, you thrive at designing large-scale systems, building complex predictive models, performing efficient experimentation and automating processes. You will partner with Architects, Product Managers and Operational Leaders for developing anti-fraud/ anti-abuse systems for our customers.

Responsibilities

In this role, you’ll:

  • Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production
  • Transform data science prototypes and applying appropriate ML algorithms and tools
  • Work closely with the Data Scientists, build tools to enhance their productivity and to ship and maintain ML models
  • Analyze huge datasets to perform EDA and come out with patterns and features to support the problem statement.
  • Manage the infrastructure and data pipelines needed to bring code to production
  • Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created
  • Partner with product managers and architects to analyse business problems, clarify requirements and define the scope of the systems needed
  • Use cloud platforms such as AWS or GCP to handle larger scale data
  • Support operational leaders by developing code to automate manual processes 
  • Drive high engineering standards on the team through code review, automated testing, and mentoring.
  • Develop white papers, blogs, reference implementations, labs, and presentations to evangelize Twilio’s design patterns and best practices for Anti-Fraud/ Anti-Abuse solutions
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:

  • Ph.D./MS/Bachelor’s in Computer Science, statistics, or related field  
  • 2+ years of applied ML experience in statistical and mathematical modeling such as supervised and unsupervised machine learning, deep learning, and/or reinforcement learning; 3+ years and a Master’s degree
  • Track record of building, shipping and maintaining machine learning systems in a highly ambiguous and fast paced environment.
  • Exposure to different ML frameworks and exposure to services like Sagemaker, Clarify, Model Monitoring, TensorFlow, MxNet, PyTorch, Sklearn, etc. preferred
  • Have hands-on experience with container orchestration frameworks (e.g. Kubernetes, EKS, ECS)
  • Familiarity with concepts related to testing and maintaining models in production such as A/B testing, retraining, monitoring model performance
  • Hands on experience with modern data storage, messaging, and processing tools (Kafka, Flink, Spark, Hadoop, Cassandra, etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar
  • Proficiency in Python is preferred. We will also consider strong quantitative candidates with a background in other programming languages such as Scala/Java

Desired:

  • Experience developing products on AWS or Google Cloud Services.
  • Experience in configuration management for deploying, configuring, and managing servers and systems.

Location 

This role will be based in our Bangalore, 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 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.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: A/B testing AWS Cassandra Computer Science Data pipelines Deep Learning DynamoDB ECS EDA Engineering Flink GCP Google Cloud Hadoop Kafka Kubernetes Machine Learning ML models MXNet Pipelines Python PyTorch SageMaker Scala Scikit-learn Spark Statistics TensorFlow Testing

Perks/benefits: Career development Competitive pay Parental leave Startup environment

Region: Asia/Pacific
Country: India
Job stats:  16  7  0

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