Staff Software Engineer, Machine Learning – Consumer Revenue

Discord

. Apply Machine Learning across Discord's core revenue surfaces — Shop, Nitro, Server Subscriptions, and Gifting.

Posted 9/22/2026full-timeRemote • United StatesLead💰 $272,000 - $340,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive experience in applied Machine Learning, with a strong focus on building and scaling ML systems from 0→1. Proficient in Python and ML frameworks, with the ability to lead cross-functional initiatives and translate data insights into strategic product decisions.

Highest-signal resume keywords

Applied Machine LearningDeep Learning ExpertisePython ProficiencyML Frameworks (PyTorch, JAX, TensorFlow)Distributed Training

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningDeep LearningRecommendation SystemsData Processing PipelinesBuilding ML SystemsExperiment AnalysisProduct Roadmap TranslationLifecycle TargetingAudience SegmentationCampaign Optimization

Soft Skills

Excellent CommunicationCollaboration SkillsLeadership

Tools & Technologies

PyTorchJAXTensorFlowRayAnyscaleChrononSparkFlink

Certifications & Qualifications

Ph.D. in Computer ScienceMaster's Degree in Machine Learning

Industry Keywords

Personalized MarketingAmbiguous EnvironmentsTechnical InitiativesProduct Teams

Tech Stack

Tools & technologies

PythonPyTorchRaySparkTensorflow

About the role

Key responsibilities & impact

Apply Machine Learning across Discord's core revenue surfaces — Shop, Nitro, Server Subscriptions, and Gifting.
Build ranking, targeting, and recommendation systems connecting users to relevant products, subscriptions, and content.
Build internal ML platforms and tooling adopted by multiple product teams.
Lead org-wide and cross-functional technical initiatives across multiple verticals.
Build ML systems from 0→1 and take them to production at scale.
Translate experiment results into product roadmap decisions.
Keep stakeholders educated and aligned.

Requirements

What you’ll need

8+ years of experience in applied Machine Learning, inclusive Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
Strong expertise in applied deep learning and mainstream RecSys model architecture (e.g. two-tower, transformer-based models, multi-task learning).
Strong proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow.
A track record of building ML systems from 0→1 in ambiguous, early-stage environments, and taking them to production at scale.
Strong product and business intuition, with the ability to translate experiment results into roadmap decisions.
Excellent communication and collaboration skills — able to lead cross-functional technical initiatives across multiple verticals and keep stakeholders educated and aligned.
The ability to thrive in ambiguous environments, energized by open-ended, technically challenging problems.
Built internal ML platform/tooling (shared data standards, targeting endpoints, recommender libraries) adopted by multiple product teams.
Familiarity with personalized marketing systems — lifecycle targeting, audience segmentation and lookalikes, campaign optimization.
Deep expertise in distributed training (e.g. PyTorch on GPU, Ray, Anyscale) and large-scale data processing pipelines (e.g. Chronon, Spark, Flink).

Benefits

Comp & perks

Equity
Benefits
Reasonable accommodations during the interview process