Staff Software Engineer, Machine Learning (Safety)

We are seeking an accomplished and experienced Staff Machine Learning Engineer – Safety ML to join our dynamic team. As a technical lead of the Safety ML team, you will be responsible for designing, developing, and maintaining our data and AI/ML infrastructure and services. You will collaborate with cross-functional teams, including data scientists, software engineers, MLEs and product managers, to deliver modern and cutting-edge solutions that improve safety on the platform. This role reports to the Senior Manager of Machine Learning, Safety.

What You'll Be Doing

• Serve as the team’s technical lead and mentor, guiding ICs through design, experimentation, and implementation while raising the technical bar.
• Define and drive the Safety ML team’s technical strategy and roadmap.
• Set the bar in technical reviews, including code, design, and architecture, ensuring the team builds scalable, robust, and high-quality ML systems.
• Collaborate cross-functionally with product, data science, policy, legal, and engineering partners to align on safety goals and deliver effective solutions.
• Tackle the most complex and high-impact challenges in safety, including adversarial abuse, harmful content detection, and evolving threat vectors.
• Develop cutting-edge safety techniques, applying state-of-the-art ML to detect and prevent harm while staying ahead of emerging abuse patterns.
• Influence the company’s direction on safety, clearly communicating trade-offs and technical constraints to senior leadership and stakeholders.

What you should have

• 5+ years of experience in ML engineering or applied ML roles.
• 2+ years of experience applying ML in Trust & Safety to counter adversarial actors.
• Strong coding skills in Python and fluency in ML frameworks such as PyTorch, JAX, or TensorFlow.
• Proven experience building performant machine learning systems at scale and have driven the execution of large, impactful projects from ideation to production.
• Ability to think from first principles, approaching complex problems with creativity, clear reasoning, and pragmatic solutions.
• A growth mindset: seeking feedback, reflecting on decisions, and continuously improving.
• Excellent communication and collaboration skills, with a history of partnering effectively across engineering, data science, legal, policy, and product teams.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field (Physics, Math, Operations Research, etc.)