Staff Machine Learning Engineer

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

WarnerMedia is a leading media and entertainment company that creates and distributes premium and popular content from a diverse array of talented storytellers and journalists to global audiences through its consumer brands including: HBO, HBO Max, Warner Bros., TNT, TBS, truTV, CNN, DC Entertainment, New Line, Cartoon Network, Adult Swim, Turner Classic Movies and others.

The Job

WarnerMedia seeks a Staff Machine Learning Engineer for the CNN.com department.

The Daily

We are looking for a Machine Learning Engineer to help us significantly scale how we experiment, build, and collaborate on ML-based data products. We are currently optimizing our first ML platform to help accelerate our experimentation and model production, and we would love for you to join us in making a huge impact on the overall organization.

Here’s some of the problems you’ll be helping us solve:

• The news cycle moves fast. What can we learn from readers’ engagement with breaking news to recommend writing or video which deepens their understanding?
• How can we create a virtuous recommender system which drives diversity in people’s reading habits?
• What’s the best way for a machine learning group to work closely with journalists and editors to keep our audience engaged and informed?

What You’ll Do

• Prototype and train new models to serve recommendations-oriented products for learning and experimentation
• Collaborate with other ML/Ops engineers to develop and improve core components, infrastructure and architecture of our ML Platform to train, deploy, and serve models at scale
• Author, test, review, and optimize production-level code in Python and Golang while executing best practices in version control and code integration
• Use and build upon open-source cloud computing technologies
• Collaborate with data scientists, engineers, product teams and other key stakeholders and drive ML projects from conception to completion

Who You Are

• You can design and build real time distributed systems for machine learning at scale.
• You have experience collaborating with data scientists, data engineers, backend engineers, and product stakeholders on machine learning products.
• You are excited about complex architecture/infrastructure for training, deploying, evaluating, and serving models, and finding ways to make all of it faster by using the latest technologies.
• You enjoy keeping up with the latest ML research but get more satisfaction from building things with real user impact.
• You understand the constraints of working with a growing team and thrive in an environment that is fast-paced and sometimes scrappy.
• You understand that serving a user-facing model comes with a set of restrictions and you know how to be creative to solve them.
• You can work independently when needed.
• You can contribute to multiple team projects simultaneously.
• You have a deep curiosity and are proactive in seeking innovative solutions to business problems.
• You are highly communicative with your team and collaborators.
• You have collaborated with others on a team to design and build web scale distributed system

Things You Should Know

• How to write robust code in Python, Golang or an equivalent modern programming language
• How to wrangle data - working with databases (relational or columnar), how to write SQL, how to work with a data pipeline, and other big data technologies and working with large data sets
• How to take a product problem and choose the right ML approach to prototype, evaluate, and tweak a solution quickly before taking it to production scale
• Commonly used machine learning frameworks (like Keras, PyTorch or TensorFlow) and libraries (like scikit-learn

Things You Might Know

• Experience with AWS and MLOps tools such as Sagemaker, MLFlow and Metaflow
• Experience with graph databases
• Experience with containerization (Docker) and container-orchestration systems such as Kubernetes
• Experience with Terraform, Azure or a similar IaC (infrastructure-as-code) tool
• If you don’t know any of these, that’s OK- you’ll get the opportunity to learn them on the job once you join!

The Perks

• Exclusive WarnerMedia events and advance screenings

• Paid time off every year to volunteer for eligible employees

• Access to well-being tools, resources, and freebies

• Access to in-house learning and development resources

• Part of the WarnerMedia family of powerhouse brands