Senior Software Engineer, Ml Platform Experience

Job Description

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 is experienced in building widely adopted 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.
Opportunities to make an impact
• Scale Metaflow to enable stronger collaboration, make engineering best practices easier for ML applications, and handle larger data & compute workloads
• Enable Research Scientists to perform offline research on 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
• Partner with ML practitioners to make their projects successful through infrastructure and thus inform the evolution of the ML Platform.
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, 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 some of: AWS, Microservices (REST or gRPC), SQL Databases, Dependency management infra (e.g., conda, artifactory), Docker, streaming technologies such as Kafka.
• You have exposure to basic ML concepts. A plus if you've built ML applications yourself.
• You actively work toward simplicity in design and implementation; you excel at channeling your colleagues' creative energy from the idea phase toward clarity and alignment. You can write concise and thought provoking technical memos.
• 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.

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

Jobcode: Reference SBJ-d890bq-18-116-42-208-42 in your application.