# Senior Software Engineer, Machine Learning (Ads)

**Company:** [Discord](https://hotfix.jobs/companies/discord)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $220k – $247k/yr
**Experience:** 5+ years
**Skills:** Python, PyTorch, TensorFlow, Machine Learning, Deep Learning, Transformers, Embeddings, A/B Testing, Recommendation Systems, Real-Time Ml Inference
**Posted:** 2026-05-07

> Develops and deploys ML models for ads targeting, ranking, and measurement on Discord's Ads platform. Requires 5+ years ML experience, 3+ years in Ads ML, Python proficiency, and PyTorch/TensorFlow expertise.

## Job Description

## What You'll Be Doing

- Design, develop, and deploy machine learning models for ads targeting and ranking.
- Develop sophisticated ML solutions such as identity graph to enhance ad targeting.
- Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, link click).
- Improve ads targeting and ranking by leveraging both on-platform and off-platform signals.
- Collaborate cross-functionally with product, engineering, and business teams to define and execute on the Ads ML roadmap.
- Scale our ML infrastructure to support an increasing number of concurrent ad campaigns while ensuring low-latency decision-making.
- Drive research and implementation of state-of-the-art ML techniques in the field of online advertising.

## What You Should Have

- 5+ years of experience as a Machine Learning Engineer or Data Scientist.
- 3+ years of experience specifically in Ads ML (ads ranking, personalization, optimization, privacy-compliant user modeling, targeting, or measurement).
- Strong proficiency in Python and familiarity with deep learning frameworks such as **PyTorch** or **TensorFlow**.
- Experience with applied deep learning (e.g transformers, embedding models).
- Proven track record of designing, implementing, and scaling ML-driven ad systems in real-world applications.
- Experience working with real-time ML inference, A/B testing, and optimization frameworks.
- Experience translating ML evaluation results and performance metrics into actionable product roadmap items.
- Ability to connect business objectives to ML solutions, with the flexibility to shift focus toward the highest-impact problems as priorities evolve.

## Bonus Skills

- Strong understanding of performance advertising and how ML impacts revenue and advertiser retention.
- Knowledge of ad tech industry standards and ads ecosystem including targeting, retrieval, ranking, pacing, frequency, auction, etc.
- Experience with large-scale recommendation systems.
- Experience with large-scale data infrastructure and distributed computing

**Compensation:** US base salary range $220,000 to $247,000 + equity + benefits.

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