Haystack News is the leading local & world news service on Connected TVs reaching millions of users! This is a unique opportunity to work at Haystack News, one of the fastest-growing TV startups in the world. We are already preloaded on 37% of all TVs shipped in the US!

Be part of a Silicon Valley startup and work directly with the founding team. Jumpstart your career by working with Stanford & Carnegie Mellon alumni and faculty who have already been part of other successful startups in Silicon Valley.

You should join us if you're hungry to learn how Silicon Valley startups thrive, you like to ship quickly and often, love to solve challenging problems, and like working in small teams.

See Haystack feature at Google IO: https://www.youtube.com/watch?v=-YawUi6qPck

Job functions

We are looking for an outstanding machine learning engineer to join Haystack and help improve the experience of millions of users that rely on Haystack to get the news every day.

Within the team you’ll find many opportunities to work on various aspects of Machine Learning and Data Engineering. The job offers the opportunity of generating a major impact on the product while working with an awesome and talented team, using the latest technologies.

You will:

Analyze large data sets to get insights using statistical analysis tools and techniques

Build, evaluate and deploy machine learning models

Maintain ongoing reliability, performance, and support of the data infrastructure, providing solutions based on application needs and anticipated growth.

Work with tools to configure, monitor and orchestrate data infrastructure and pipelines.

Run and monitor AB Tests

Build and manage APIs

Qualifications and requirements

Bachelor's degree in Computer Science, Statistics, Math or related field.

3+ years experience writing software in a professional setting

Knowledge of AWS and Python

Strong Math/Stats background with statistical analysis experience on big data sets

Experience with SQL and NoSQL (e.g. MongoDb or DynamoDB)

Big Plus: Experience with data warehouses (e.g. Snowflake, Big Query, Redshift)

Exposure to ML/AI libraries such as sklearn, LightGBM and, XGBoost.

Travel Visa to the US (desired)

Conditions

Uber rides to come to the office!

Travel to team's offsite events

Learn about multiple technologies