Senior Software Engineer, Machine Learning (Safety)

• →Analyze data to identify risk patterns and inform the design of machine learning models
• →Build, iterate on, and evaluate models that detect risk and anomalous behavior
• →Work with product, engineering, legal, and Trust and Safety partners to deliver effective ML solutions
• →Work with partner teams in Trust & Safety to curate golden label sets at scale and improve data labeling techniques for model training
• →Deploy models into production systems, writing backend code as needed to ensure scalability and reliability, and monitor performance
• →Document modeling approaches and systems, and apply current machine learning best practices

• 4+ years of experience in ML engineering or applied ML roles.
• Strong coding skills in Python and fluency in ML frameworks such as PyTorch, JAX, or TensorFlow.
• Experience building performant machine learning systems at scale and have driven the execution of 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.

The US base salary range for this full-time position is $220,000 to $247,500 + 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.

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