Staff Software Engineer, Machine Learning – Consumer Revenue

Posted Sep 22

This is a fully remote position, open to applicants in United States.

📋 Description

• Utilize Machine Learning across Discord's primary revenue channels — Shop, Nitro, Server Subscriptions, and Gifting.

• Develop ranking, targeting, and recommendation systems that connect users with relevant products, subscriptions, and content.

• Create internal ML platforms and tools that are embraced by multiple product teams.

• Spearhead organization-wide and cross-functional technical projects across various sectors.

• Construct ML systems from inception to production at scale.

• Convert experimental findings into strategic product roadmap decisions.

• Ensure stakeholders are informed and aligned.


⛳️ Requirements

• Over 8 years of experience in applied Machine Learning, including a Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline.

• In-depth knowledge of applied deep learning and standard RecSys model architectures (e.g., two-tower, transformer-based models, multi-task learning).

• Strong command of Python and ML frameworks such as PyTorch, JAX, or TensorFlow.

• Proven experience in building ML systems from inception to production in ambiguous, early-stage settings.

• Solid product and business intuition, with the capability to translate experimental outcomes into roadmap decisions.

• Exceptional communication and collaboration skills — capable of leading cross-functional technical projects across various sectors while keeping stakeholders informed and aligned.

• Ability to excel in ambiguous settings, motivated by open-ended, technically challenging issues.

• Developed internal ML platforms/tools (shared data standards, targeting endpoints, recommender libraries) adopted by multiple product teams.

• Familiarity with personalized marketing systems — lifecycle targeting, audience segmentation, lookalikes, and campaign optimization.

• Extensive expertise in distributed training (e.g., PyTorch on GPU, Ray, Anyscale) and large-scale data processing pipelines (e.g., Chronon, Spark, Flink).


🏝️ Benefits

• Equity

• Benefits

• Reasonable accommodations during the interview process

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