Machine Learning Engineer - Safety Product
San Francisco, California, USA
Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...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 outstanding esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate and grow their personal interests and passions. We're always live at Twitch. Continually learn about all things Twitch on Linkedin, Twitter and on our Blog.
About the Role:
Are you passionate about making Twitch safer, more inclusive, and a nicer place to enjoy? This position lets you do exactly that! You will be part of a rapidly growing Machine Learning team which develops and deploys algorithms that are the first line of defense of users' safety at Twitch. You will work with passionate co-workers who live Twitch's mission and put their hearts into their work. If this sounds like an environment where you will thrive, come and join our team!
You Will:
· Build machine learning products in the safety world to protect Twitch from bad behavior such as followbotting, spam, phishing, and violent or illegal content
· Design and build scalable infrastructure that enables deploying machine learning models on petabytes of data
· Develop data pipelines and other modern big data processing systems
· Build distributed services to power machine learning solutions
· Design databases and make storage choices for efficient ML data management
· Bring operational excellence to MLOps/DevOps
· Work on event-driven data flows to evolve machine learning applications
· Partner with fellow engineering and science teams to accomplish complex projects together
Basic Qualifications
You Have:
· Bachelors in Computer Engineering/Science or equivalent
· Outstanding programming skills
· Demonstrated ability to understand and contribute to large software systems
· Experience building distributed services or backend services and understand scaling computation to thousands of machines
· Passion for machine learning
Preferred Qualifications
Bonus Points:· 2+ years of industry experience or equivalent internship experience
· Experience working with Amazon Web Services or other cloud solutions
· Experience with ML libraries/frameworks such as Keras, Tensorflow, and AWS Sagemaker
· Understanding of MLOps or DevOps concepts
· Experience working with large-scale data and orchestration tools such as Airflow, AWS Stepfunctions and Kubeflow
· Experience with streaming data and event-driven systems, and knowledge tools like Kinesis, Kafka, Flink, Spark, RabbitMQ and SQS
· You are a Twitch user who cares about safety
Perks:
· 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
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
Tags: Airflow AWS Big Data Data management Data pipelines DevOps Engineering Flink Kafka Keras Kinesis Machine Learning ML models MLOps Pipelines SageMaker Spark Streaming TensorFlow
Perks/benefits: Career development Fitness / gym Flex hours Flex vacation Health care Insurance Lunch / meals Medical leave Parental leave Salary bonus Snacks / Drinks Team events
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