Staff Machine Learning Engineer - Risk and Trust

What you'll do

• Identify ML opportunities and help shape the team's technical roadmap with product, data science, and engineering partners.
• Design and build robust ML solutions, owning their lifecycle from data preparation and modeling through testing, deployment, and monitoring.
• Lead complex ML initiatives, promote engineering best practices, and mentor other machine-learning engineers.

What they ask for

• 8+ years of industry experience developing machine-learning models and deploying ML solutions to production.
• Master's degree in a related technical field.
• Strong foundation in machine-learning algorithms, statistics, and optimization; demonstrated application of ML to complex, large-scale real-world problems.
• Proficiency in Python and experience with modern ML frameworks, large-scale data pipelines, and distributed data processing.

Nice to have

• PhD in a related technical field.
• Experience with advanced ML techniques or ML for fraud detection, anomaly detection, adversarial environments, or large-scale real-time systems.

Pay

USD $232,000 per year - USD $258,000 per year base salary (San Francisco, CA); USD $232,000 per year - USD $258,000 per year base salary (Sunnyvale, CA)

Tools

Python, PyTorch, TensorFlow, JAX, Spark, SQL

AI focus

Builds machine-learning risk and fraud prevention systems, including responses to increasingly sophisticated AI-driven attacks; preferred experience includes large language models.