Senior Software Engineer, Generative AI, Ads Safety

• Write and test product or system development code.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Engineer a sophisticated toolkit for the automated model training lifecycle, deploying AI agents to automate model evaluation and prompt optimization, effectively removing human intervention from the critical path of model development.
  
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Design and implement end-to-end (E2E) ML architectures for Ads Safety, including developing robust capabilities for automated model refreshing, high-scale data pipelining/funneling, and proactive signal integration to improve overall detection quality.
  

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development, applied ML, autonomous systems, and large-scale systems design.
• 3 years of experience with end-to-end machine learning (e.g., model building, model deployment, model evaluation, optimization, data processing, and debugging).
• 3 years of experience with one or more of the following machine learning specializations: Multi-Modal LLMs, Computer Vision, NLP, Reinforcement Learning.
• 1 year of experience with GenAI techniques (e.g., Agentic Workflows, RAG, ICL, or RSI).
  

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures and algorithms.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development, applied ML, autonomous systems, and large-scale systems design.
• 3 years of experience with end-to-end machine learning (e.g., model building, model deployment, model evaluation, optimization, data processing, and debugging).
• 3 years of experience with one or more of the following machine learning specializations: Multi-Modal LLMs, Computer Vision, NLP, Reinforcement Learning.
• 1 year of experience with GenAI techniques (e.g., Agentic Workflows, RAG, ICL, or RSI).