Machine Learning Engineer
hace 2 días
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.
**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
- 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
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