Staff Software Engineer, Machine Learning Platform

The Machine Learning Platform team at Discord is responsible for the end to end model development lifecycle across all ML applications. We work closely with machine learning engineers, core infrastructure, and ML consumers to deliver the tools, services, and frameworks that make machine learning training and deployments easy, safe, scalable, and accessible. In this role, you’ll work on everything from training and batch inference pipelines, online model serving, feature stores, event stream processing, and LLM serving and evaluation. You’ll lead projects and partner with ML practitioners and other Staff+ engineers to shape the future of Discord’s data infrastructure. This role reports to the Senior Engineering Manager of the ML Platform team.

What You'll Be Doing

• Design and build the platform that ML engineers and data scientists rely on to deliver delightful user experiences and keep communities safe
• Evaluate and integrate new ML frameworks and tools to ensure Discord stays at the forefront of a fast-moving field, including LLMs and generative AI
• Partner with model builders to help them ship high-quality models quickly and often
• Champion best practices in feature engineering and ML infrastructure
• Build and maintain shared ML foundations, including datasets and embedding models, that elevate the overall quality of ML applications

What you should have

• 8+ years of experience as a software or ML engineer, working with large-scale data or distributed systems
• 4+ years of experience building platforms and infrastructure primarily used by engineering stakeholders
• 2+ years of experience building machine learning platforms that support the full model lifecycle, including orchestration systems (e.g. Dagster, Flyte, or Airflow)
• Proven ability to establish and execute on clear, actionable, and accurate technical direction beyond the next month or quarter
• Experience leading technical initiatives across teams with diverse resources, skillsets, and priorities

Bonus Points

• Experience operating, monitoring, and maintaining large-scale production systems, especially on Kubernetes and/or in large data domains
• Experience with real-time data processing (e.g. Kafka, Spark, or Flink)
• Experience building ML models using modern frameworks (e.g. PyTorch, TensorFlow, or JAX)
• Experience deploying GenAI applications, eval frameworks, or agents
• Experience managing infrastructure costs by designing for efficiency and scalability

The US base salary range for this full-time position is $272,000 to $306,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.