Machine Learning Engineer 2
Bengaluru, India
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.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 modeling 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 analyze 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 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 accommodation@twilio.com.
* 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 Java Kafka Kubernetes Machine Learning ML models MXNet Pipelines Python PyTorch Reinforcement Learning SageMaker Scala Scikit-learn Spark Statistical modeling Statistics TensorFlow Testing
Perks/benefits: Career development Competitive pay Health care Medical leave Parental leave Startup environment
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