Netflix

Los Gatos, CA
5,001-10,000 employees
Netflix is the world's leading streaming entertainment service

Senior Software Engineer, Machine Learning Platform Experience

Senior Software Engineer, Machine Learning Platform Experience

This job is no longer open

For Netflix, success means entertaining the world: the 200M members we have today, the next 300M members and beyond. Machine Learning plays a vital role -- from personalizing the experience for each member to improving how we bring content from around the world onto the Netflix service. Doing this at scale while rapidly innovating is far from sorted out. The ML Platform Experience (MLX) team exists to enable the people who do ML and Data Science at Netflix to have the most productive and prolific periods of their careers. Over the past several years we developed Metaflow to make Data Scientists more productive, but our work has just begun.

The MLX team is looking for a Senior Software Engineer who can help us build first generationbandits & Reinforcement Learning infrastructure for a growing set of explore/exploit algorithms in personalization, messaging, growth and beyond.

Opportunities to make an impact:

• Help define our technical vision for bandit infrastructure - from logging to training to serving

• Accelerate the process of standing up a new bandit/RL algorithm and increase our capacity to experiment

• Scale the work of ML Engineers by providing centrally leveraged infrastructure

About Us

We are a small team with diverse backgrounds. We come from 3 continents and have a range of technical experience: from building large scale mission critical services to Computer Vision research to crafting delightful user experiences to building production search & recommendations systems. Collectively, we have decades of experience building ML platforms. We share a passion for helping humans become more productive. We find strength in diversity because it will make us better at entertaining the world. Inclusion is threaded into the daily work we do; we make space for everyone on the team to do their best work, and we hope that you'll be able to envision yourself working with us.

Our values:

  • We fanatically support all ML practitioners so that they can succeed
  • We walk in the shoes of our users to guide our work through empathy
  • We start slow to take our users farther, rather than moving fast and breaking things
  • We treat technology as a means to improve the practice of ML, not a goal in itself
  • We make an impact equally through big efforts and many small wins

About You

You're passionate about helping humans become more productive. Our team values resonate with you, and perhaps you've been living them. You believe that when it comes to building solid platforms, the code and the build artifacts are just the beginning. You consciously prioritize approachable documentation, responsive customer support, rock solid operations, and extensive, repeatable testing. You possess the skills below.

• You're fluent in a mainstream programming language (Python, Java, Scala, Golang, C++ or similar) and comfortable working in a polyglot environment. You have working knowledge under the hood of your primary language down to the OS level (e.g., compiler/interpreter, filesystem, concurrency, memory).

• You've built widely adopted infrastructure for technical users (ideally ML practitioners or data consumers/producers). A plus if you've worked with Spark.

• You can leverage your maths/stats background to quickly dive into academic papers on multi-armed bandits and Reinforcement Learning. A plus if you already have experience with RL or bandits.

• You can quickly survey and make sense of complex systems. For example, mapping out the data flow across interlocking microservices.

• You are a cross-functional technical leader; you're able to rally not only the technology but the people involved in bringing new systems to life that span multiple teams.

We look forward to discussing more aboutNetflix culture, our approach to Inclusion & Diversity and what it's like to work at Netflix.

This job is no longer open
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