For Netflix, success means entertaining the world: the 200M members we have today, the next 300M members and beyond. Machine Learning and Data Science play 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 finds joy and fulfillment in making technical and scientific users productive through infrastructure, and has had exposure to Machine Learning concepts in their day-to-day work.
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.
Opportunities to make an impact
- Increase the scale of data and models and improve SLAs for Metaflow users
- Enable Data Scientists to research novel product-facing algorithms (think: Netflix prize or kaggle for internal grand challenges)
- Build infrastructural bridges between the JVM-based world of rich fact and feature data into the Python-based world of state-of-the-art ML frameworks
- Develop recipes and patterns that Data Science teams across the organization can apply to better operate their ML projects
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
Examples of what the team is working on
- Providing smooth onramps for researchers to prove their ideas in the Netflix customer experience
- Providing standard monitoring and insights into model quality and robustness
- Making common AB tests easy (e.g., feature tests or model architecture tests)
- Helping to enable Explore/Exploit as a scalable testing methodology
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, extensive, repeatable testing and/or accessible user education. You excel at some of the skills listed below, and are excited to master the rest.
• We operate in a polyglot environment with Python and Scala and some C++. We expect you to be fluent in one of these or a similar language.
• Ideally you've built practical ML or Data Science projects, but if not we'd like you to be familiar with basic ML concepts
• Preferably, you've built widely adopted ML infrastructure, but if not, you've worked in overlapping areas, such as distributed systems, productivity tooling or data infrastructure
• You excel in at least one mode of communication, such as giving presentations, writing technical memos, storytelling, or keeping the team up-to-date via slack.
• You navigate ambiguity well. For example, your team relies on you to make high-stakes choices about what is the right thing to build (or buy) and what to say no to. Or, your users rely on you to guide them through multiple possible solutions to their business problem.
We look forward to discussing more aboutNetflix culture, our approach to Inclusion & Diversity and what it's like to work at Netflix.