Machine Learning Engineer, GenAI Applied ML

Job Description

Scale AI is seeking a Machine Learning Engineer to join their team and lead the development of machine learning systems focused on detecting fraud, abuse, and trust violations across Scale’s contributor platform. This role is crucial for ensuring the quality, safety, and reliability of data used to train and evaluate frontier models within the Generative AI data engine. The Machine Learning Engineer will collaborate with engineering, product, and operations teams to proactively identify misuse, defend against adversarial behavior, and maintain the health of human-in-the-loop data workflows.

• Designing and deploying machine learning models to detect fraud, quality issues, and violations in large-scale contributor workflows
• Building real-time and batch detection systems that evaluate account, behavioral, and content-level signals
• Combining traditional ML techniques with LLMs and neural networks to improve detection capabilities and reduce false positives
• Creating robust evaluation frameworks and actively tuning for extremely imbalanced detection scenarios
• Collaborating closely with product and engineering teams to embed detection systems into contributor-facing workflows and backend infrastructure

• 3+ years of experience building and deploying ML models in production environments
• Experience with trust & safety, fraud detection, abuse prevention, or adversarial modeling in a real-world setting
• Proficiency in ML and deep learning frameworks such as scikit-learn, PyTorch, TensorFlow, or JAX
• Familiarity with LLMs and experience applying foundation models for structured downstream tasks
• Strong software engineering fundamentals and experience building ML systems in microservice architectures (e.g., using AWS or GCP)
• Excellent communication skills and a proven ability to work cross-functionally

• Comprehensive health, dental and vision coverage
• Retirement benefits
• A learning and development stipend
• Generous PTO