Multimodal Safety (AI)

Location: London, Mountain View, New York City, or Zurich

Base pay: USD $119,800–$234,700 per year across the U.S.; USD $160,200–$261,000 per year in the San Francisco Bay Area and New York City metropolitan area.

Company

Microsoft AI builds AI systems and products focused on frontier model development, product engineering, and responsible AI.

What you will do

• Develop learned classifiers, policy models, prompt-based safeguards, and runtime guardrails for multimodal models.
• Build training and evaluation datasets using synthetic generation, red teaming, product feedback, and real-world traffic.
• Design evaluations for harmful or deceptive generated media, unsafe image transformations, policy evasion, adversarial inputs, and emerging image and audio use cases.
• Convert incidents and partner feedback into repeatable test cases and regression suites, then diagnose failures and improve models, policies, and products.
• Monitor deployed safeguards across traffic sources, customers, models, and product configurations.
• Partner with production, serving, research, product, policy, privacy, and Responsible AI teams on Azure-based deployment and safety strategy.

Requirements

• Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
• Experience developing, adapting, or evaluating modern machine learning systems.
• Strong programming skills in Python.
• Experience designing experiments, defining metrics, running ablations, and making evidence-based technical decisions.
• Experience building data pipelines, including dataset construction and annotation.
• Experience with reproducible ML workflows, version control, configuration management, automated testing, and experiment tracking.

Nice to have

• Experience with diffusion models, autoregressive media models, audio-generation systems, or image and audio editing architectures.
• Experience building image or audio safety classifiers, content-understanding systems, trust and safety models, policy engines, or guardrails.
• Experience with Azure or another major cloud platform, GPU capacity planning, model APIs, monitoring, and rollback.
• Experience with production analytics and observability tools such as Azure Data Explorer, Kusto, or Datadog.
• Experience with red teaming, adversarial evaluation, interpretability, robustness, privacy, security, policy development, or responsible AI.

Culture & Benefits

• Work spans research and production environments.
• Collaboration includes research, engineering, product, policy, privacy, security, and Responsible AI disciplines.
• Eligible roles may include benefits and other compensation.
• Applications are accepted on an ongoing basis until the position is filled, with the role open for at least five days.