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About the Role

We are seeking a Member of Technical Staff to enhance safety for generative-media models and products, specifically focusing on image generation and editing. You will develop model-based classifiers, runtime guardrails, evaluations, and data to ensure these systems produce creative and useful content while adhering to safety policies. This role involves working across research and production, identifying and diagnosing emerging failure modes, improving guardrails and policies, and collaborating with product and platform teams for large-scale safeguard deployment and monitoring. This position is ideal for an ML or software engineer with a passion for generative image systems, strong experimental judgment, and a practical grasp of safety policy, creative quality, overblocking, latency, and real-world deployment challenges.

Responsibilities

Develop and improve learned classifiers, policy models, prompt-based safeguards, and other runtime guardrails for MAI's multimodal models.
Build high-quality training and evaluation datasets from synthetic generation, red teaming, product feedback, and real-world traffic while maintaining appropriate controls.
Design evaluations for harmful or deceptive generated media, unsafe image transformations, policy evasion, adversarial inputs, and emerging image and audio product use cases across both request and output paths.
Turn incidents and partner feedback into repeatable test cases and regression suites.
Diagnose failures, then translate findings into durable model, policy, or product improvements.
Monitor deployed safeguards across traffic sources, customers, models, and product configurations.
Partner with Production Safety and serving teams on Azure-based deployments, capacity planning, and guardrails integration.
Partner with Safety Alignment, Safety Engine, model, product, policy, privacy, and Responsible AI teams to adjudicate ambiguous cases and define end-to-end safety strategies.
Contribute reusable guardrail libraries, documentation, deployment and monitoring runbooks, technical standards, and operational practices for generated-media safety.

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.
Ability to design experiments, define metrics, run ablations, and make evidence-based technical decisions.
Experience building data pipelines, including dataset construction and annotation.
Experience developing reproducible ML workflows using version control, configuration management, automated testing, and experiment tracking.
Ability to collaborate across research, engineering, product, and policy disciplines and communicate technical tradeoffs clearly.

Skills

Generative image systems
ML systems development
Software engineering
Python programming
Experimental design
Data pipelines
ML workflow development
Diffusion models
Autoregressive media models
Audio-generation systems
Image safety classifiers
Content-understanding systems
Trust and safety models
Policy engines
Input and output guardrails
Generated-media safety risks
Adversarial inputs
Unsafe generation or editing
Harmful-content transformation
Impersonation or deceptive media
Privacy violations
Policy evasion
Azure cloud platform
Azure AI services
Azure Machine Learning
Model APIs
GPU capacity planning
Versioning
Monitoring
Rollback
Red teaming
Adversarial evaluation
Interpretability
Robustness
Privacy
Security
Policy development
Responsible AI

Location

U.S.

Work Type

Full-time

Experience Level

Member of Technical Staff
IC4

Education Level

Bachelor’s degree in Computer Science, Engineering, or related technical field, or equivalent practical experience.

Salary/Compensations

USD $119,800 - $234,700 per year (U.S. typical base pay range)
USD $160,200 - $261,000 per year (San Francisco Bay area and New York City metropolitan area)

Benefits

Certain roles may be eligible for benefits and other compensation.

About the Company

Microsoft AI is building AI systems and products that empower people’s lives.
Our work is driven by a community of brilliant, interdisciplinary minds working across frontier model development, product engineering, and responsible AI.
Within Microsoft AI, the Safety team develops the training methods, evaluations, runtime safeguards, monitoring, and infrastructure needed to make advanced AI systems safer, more reliable, and more useful.
Our work spans text, multimodal, and agentic systems and is developed in close partnership with other Research teams, Production Inference, Security, Responsible AI, Microsoft product organizations, and external partners and customers.

Equal Opportunity

Microsoft is an equal opportunity employer.
All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.
If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.