Senior Software Engineer, Machine Learning Platform
140k - 155k USD
Hybrid
Full Time
#Software Engineering
#Machine Learning
#Infrastructure
#MLOps
#DevOps
#Kubernetes
#Docker
The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for.
About the Role
Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.
The Machine Learning Platform (MLP) team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements (SLAs) guaranteed by the MLP.
We are looking for a Senior Software Engineer, with a focus on MLOps, to join our Machine Learning Platform team to help solve creative challenges around Machine Learning infrastructure for the New York Times.
Hybrid work schedule based in New York City reporting to the engineering manager of the Machine Learning Platform team.
Responsibilities:
- You will research, develop, and deploy infrastructure for the Machine Learning Platform that supports large scale multi-tenant workloads
- You will build a platform to train and test algorithms that provide real-time content recommendations and personalization to our readers
- You will enhance ML platform’s CI/CD and integration testing capabilities
- You will be part of building a platform to empower data scientists with self-service patterns that support the full ML workflow from model training and testing to production deployment at high scale and low latency across our products
- Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.
Basic Qualifications:
- 4+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment
- Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)
- Experience working with Kubernetes, Docker, and CI/CD (Drone, Argo, Jenkins,etc)
- Experience leading the development of large scale, data driven, distributed multi-tenant systems
- Proficiency with at least one high-level programming language like Python or Go
Preferred Qualifications:
- Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, BigTable or other NoSQL datastores such as Cassandra, DynamoDB, Redis
- Familiarity with ML tooling such as Triton, TensorFlow, scikit-learn
- Experience building the infrastructure that power real-world machine learning applications like recommendation systems, bandits, etc.
- Experience engaging with partners to understand pain points, observe patterns, and identify opportunities for improvements
This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.
REQ-017430
The New York Times is committed to a diverse and inclusive workforce, one that reflects the varied global community we serve. Our journalism and the products we build in the service of that journalism greatly benefit from a range of perspectives, which can only come from diversity of all types, across our ranks, at all levels of the organization. Achieving true diversity and inclusion is the right thing to do. It is also the smart thing for our business. So we strongly encourage women, veterans, people with disabilities, people of color and gender nonconforming candidates to apply.
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