Staff Software Engineer, Machine Learning (Consumer Revenue)
About this role
Discord needs to connect millions of active gamers more effectively to core revenue features like the Shop, Nitro, and server subscriptions, which requires sophisticated ranking and recommendation systems. The Consumer Revenue machine learning team builds these targeting architectures from the ground up, scaling them to handle complex personalization and marketing campaigns across the platform.
As a senior technical owner on this team, the engineer will drive foundational ML infrastructure and shape monetization strategies in an ambiguous environment. The right candidate brings extensive experience designing large-scale recommender systems, mentoring cross-functional stakeholders, and translating experimentation directly into product roadmaps.
What you will do
- Design and deploy machine learning ranking, targeting, and recommendation systems for core revenue surfaces including the Shop, Nitro, and server subscriptions.
- Build machine learning systems from zero to one within early-stage environments and scale them to production.
- Drive org-wide technical initiatives by collaborating across multiple product verticals and maintaining stakeholder alignment.
- Translate experimental results and business metrics into actionable roadmap decisions.
- Develop internal machine learning platforms, shared data standards, and recommender libraries for adoption by multiple teams.
What you need
- Bring eight or more years of professional experience in applied machine learning, which can include a Ph.D. or Master's degree in computer science or a related technical field.
- Demonstrate strong expertise in applied deep learning and mainstream recommender system architectures such as two-tower or transformer-based models.
- Show proficiency using Python alongside major machine learning frameworks like PyTorch, JAX, or TensorFlow.
- Possess a proven track record of taking zero-to-one machine learning systems to production at scale.
- Exhibit strong product and business intuition with the capability to lead cross-functional technical initiatives.
Nice to have
- Built internal ML platform and tooling adopted by multiple product teams
- Familiarity with personalized marketing systems including lifecycle targeting and campaign optimization
- Deep expertise in distributed training like PyTorch on GPU, Ray, or Anyscale
- Experience with large-scale data processing pipelines such as Chronon, Spark, or Flink
Benefits
- Equity
- Benefits
Skills and tech stack
Questions candidates ask
Where is this job located?
This position is US-based and can be remote. Employees who live in the San Francisco Bay Area are also welcome to work from the office.
What is the salary range for this role?
The US base salary range for this full-time position is $272,000 to $340,000. Individual pay within this range is determined by factors including job-related skills, experience, and relevant education or training.
What does total compensation include beyond base salary?
Compensation details listed in US role postings reflect the base salary only and do not include equity or benefits, which are also part of the package.
What kind of systems will I be building?
You will apply machine learning across core revenue surfaces like the Shop, Nitro, Server Subscriptions, and Gifting. This involves building ranking, targeting, and recommendation systems that connect users to the right products and content.