This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.

Role Description

This role offers a unique opportunity to shape the future of trust and safety across a large-scale, high-impact platform. As a senior technical contributor, you will:

• Design, build, and productionize cutting-edge Machine Learning and Agentic AI models to detect and prevent fraud, protect users, and enhance overall platform safety.
• Influence long-term ML strategy and drive large-scale initiatives across multiple teams.
• Mentor other engineers while remaining hands-on in coding and model deployment.
• Contribute directly to protecting the community and improving operational outcomes at scale.

Accountabilities:

• Define and execute the long-term Machine Learning technical vision for trust and safety initiatives, identifying key investments and championing best practices.
• Lead the design, development, and productionization of ML models and pipelines, including batch and real-time use cases for anomaly detection, risk evaluation, and generative AI applications.
• Drive multi-quarter, cross-team ML projects, ensuring alignment across product, platform, and trust engineering roadmaps.
• Mentor and provide technical guidance to other ML and software engineers on complex architectural, modeling, and production challenges.
• Collaborate with cross-functional partners—including software engineers, data scientists, and product managers—to translate requirements into scalable ML solutions.
• Continuously evaluate emerging AI/ML technologies to advance capabilities, model performance, and operational reliability.
• Contribute hands-on code and actively participate in building robust, scalable, and maintainable ML systems.

Qualifications

• 12+ years of industry experience in applied Machine Learning, with 2–3+ years working with LLMs and generative AI technologies, including Agentic AI frameworks.
• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related field.
• Strong programming skills in Python, Scala, Java, C++, or equivalent, with solid data engineering expertise.
• Deep understanding of ML best practices (training/serving skew minimization, feature engineering, model selection) and algorithms (gradient boosted trees, neural networks, deep learning).
• Hands-on experience with ML frameworks and tools such as TensorFlow, PyTorch, and Kubernetes, as well as end-to-end ML infrastructure and production systems.
• Familiarity with large-scale software application architecture, including APIs, high-volume data pipelines, and efficient model deployment.
• Experience with test-driven development, A/B testing, and incremental deployment.
• Prior experience in Trust, Risk, fraud detection, or safety domains is a plus.
• Excellent collaboration, communication, and mentoring skills.

Benefits

• Competitive base salary range: $244,000 – $305,000 USD, dependent on experience and skills.
• Performance-based bonuses, equity, and other incentive programs.
• Comprehensive health, dental, and vision insurance coverage.
• Flexible remote work options and paid time off.
• Access to advanced AI/ML tools, high-scale platforms, and cutting-edge technologies.
• Opportunities for career growth, skill development, and mentorship in a highly innovative environment.

Company Description