Staff Software Engineer, Machine Learning Infrastructure

Key Skills

Python Programming, AWS, Apache Hadoop, Apache Kafka, Machine learning techniques, Apache Cassandra, PyTorch, TensorFlow, Apache Airflow, Docker, Kubernetes-K8s, Google Cloud Platform (GCP), Terraform, ScyllaDB, SPARK Programming, Apache Flink, Search Relevancy, Content Generation, Personalization, Open source project tools

Job Description

The ML Platform Team at Discord is focused on creating a state-of-the-art Machine Learning platform to power features used by millions of Discord users everyday. We work with our Applied ML teams to adapt and scale cutting-edge ML techniques to unlock new possibilities within areas such as trust and safety, user engagement, and revenue growth.

As a Machine Learning Engineer at Discord, you will have the unique opportunity for massive impact as you will build systems that are the backbone of features that enhance the experience for all of Discord's users. You'll influence important strategic decisions across all Discord product teams by bringing a unique perspective to projects while streamlining and promoting the application of machine learning at Discord.

What You'll Be Doing

• Design and build robust, high-scale machine learning systems that power product features used by millions of users every day.
• Develop frameworks and services; evangelize best practices for deploying and operating reliable ML-driven systems.
• Mentor and teach: raise the infrastructure sensibility and operational awareness of the machine learning teams at Discord.
• Build efficient solutions on top of Google Cloud Platform using Python, Scala, and Rust.

You'll Thrive in This Role If...

• You have 10+ years of experience as a Software Engineer.
• 8+ years professional experience, or PhD in a quantitative field including Computer Science, Physics, Applied Math, Statistics or other quantitative fields.
• Experience leading complex technical projects with successful outcomes
• Experience building, deploying, and operating large-scale distributed systems: it makes you uncomfortable deploying something for end-users without considering important performance metrics, monitors and dashboards, graceful degradation and feature flags.
• Experience with common languages used for machine learning practice such as Python and familiarity with frameworks like PyTorch and TensorFlow.
• Experience with or willingness to learn about machine learning practice in areas such as Text Classification, Semantic Modeling, Ranking and Personalization.
• You are a first principles thinker that can work with others to come up with pragmatic solutions — and then evolve and generalize them.
• You can take a high-level goal and deliver a shippable solution.

Bonus Points

• Experience with large-scale personalization, search, or content moderation systems.
• Experience with open source and managed data products like Kafka, Spark, Flink, Cassandra/Scylla, Hadoop, Airflow, etc.
• Experience with cloud infrastructure (Google Cloud, AWS, etc) and Kubernetes/Docker.
• Experience with infrastructure management tooling like Terraform and build systems.

New York City residents only: Minimum salary of $214,000/year + equity and benefits
*Note: Disclosure as required by NYC Pay Transparency Law

Colorado residents only: Minimum salary of $171,200/year + equity and benefits
*Note: Disclosure as required by sb19-085(8-5-20).

Benefits and Perks

• Comprehensive medical insurance including Health, Dental and Vision (plus up to $20,000 for gender affirmation procedures)
• Mental health resources and quarterly wellness stipends
• 16+ paid holidays, 4 weeks of PTO + use-what-you-need sick days
• Paid parental leave (plus fertility, adoption and other family planning benefits)
• Flexible long-term work options (remote and hybrid)
• Volunteer time off
• A diverse slate of Employee Resource Groups
• Plus commuter contributions and other perks for office-based employees