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Monthly
€15,915 - €19,894
Posted August 28, 2026 · 0 days agoLast seen August 27, 2026Est. expiry October 2, 2026

Senior Software Engineer

How this salary compares
Salary Context: Senior Software Engineer

Hover or tap a row for full statistics (EUR / month on this chart).

Salary analysis

Compared with the selected benchmark ("All roles in San Francisco, United States"), this listing's salary midpoint is about 54% higher. The offer sits above the benchmark range (€10,707–€16,060). The listed pay band (€18,333–€22,917) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 3 comparable listings.

Monthly salary comparison for Senior Software Engineer
MarketLower bound (25th percentile)MedianUpper bound (75th percentile)
Market Average: Senior Software Engineer€3,500/per month€5,889/per month€12,323/per month
All roles in San Francisco, United States€10,707/per month€14,107/per month€16,060/per month
About the role

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 The US base salary range for this full-time position is $220,000 to $275,000 + 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.

Job Details

Responsibilities

  • 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
  • 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

Requirements

  • 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

Skills & Technologies

PythonPyTorchTensorFlowMachine LearningA/B testingReal-time inferenceEmbeddingsTransformers
Seen 2 days agoPartial Schema
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Discord · 1 open roles
Top locations: Remote - Global · 1
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Remote - Global1
Current role mix at Discord on JobCrawls
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Engineering Manager1
Current role-level mix at Discord on JobCrawls
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