(Closed) Senior Machine Learning Infrastructure Engineer - Community Health
Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on LinkedIn, Twitter, and on our Blog.
About The Role
We are looking for a proven Machine Learning Infrastructure Engineers who are excited to solve challenging and open-ended problems in the creation of automated safety products. As a Machine Learning Infrastructure Engineer on our Trust & Safety team, you will build systems which help us better understand user behaviors and several types of user-generated content. Reporting to the Director of Engineering, you will develop infrastructure for next-generation intelligent products using Machine Learning models with an outstanding applied science team. You will help ensure that creators and viewers on Twitch can build thriving communities by eliminating negative interactions (harassment, inappropriate content, etc).
- Design and build scalable infrastructure that enables deploying machine learning models over billions of historical data points collected from petabytes of data
- Develop data pipelines powered by AWS Sagemaker and other modern big data processing systems.
- Develop performant data backend consisting of transactional, analytic, and NoSQL databases.
- Helping maintain tools for monitoring the performance of machine learning models at scale and ensuring the integrity of incoming data feeds.
- Build and maintain performant distributed systems services and large-scale applications
- Embrace and champion engineering best practices within your group and beyond
- Produce clean, high-quality code, tests, and well written documentation
- Contribute engineering input and feedback into product planning processes
- Partner with fellow engineering and science teams to accomplish complex projects together
- Bachelors in Computer Engineering/Science or equivalent.
- Outstanding programming skills. Demonstrated ability to design and lead large software systems.
- Deep knowledge of distributed systems. Experience with modern big data frameworks, especially in the context of building data pipelines. Experience in scaling computation to thousands of machines, ideally in the context of machine learning.
- Experience working with Amazon Web Services, in addition to Google Cloud, and other cloud providers. A solid understanding of machine learning and/or DevOps expertise is a plus.
- 7+ years of work experience or relevant experience with a PhD in CS or related field
- 2+ years of work experience building large-scale production Machine Learning systems or extensive experience with building distributed systems and willingness to learn specifics of ML systems
- Experience with ML libraries/frameworks such as Keras, Tensorflow, AWS Sagemaker
- Experience of software development in one or more of the general purpose programming languages: Go, Python, Java, C/C++
- Desire and ability to write production-quality code
- MS or PhD in CS or related field
- Familiarity with AWS services
- In-memory key value stores such as Memcache, Redis
- SQL and NoSQL databases
- AWS Kinesis or Kafka data streams
- Medical, Dental, Vision & Disability Insurance, 401(k) , Maternity & Parental Leave , Flexible PTO, Commuter Benefits, Amazon Employee Discount, Monthly Contribution & Discounts for Wellness Related Activities & Programs (e.g., gym memberships, off-site massages , etc. ), Breakfast, Lunch & Dinner Served Daily, Free Snacks & Beverages
We are an equal opportunity employer and value diversity at Twitch. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.