Job description

Join Adobe Security Engineering and help build the ML and generative AI capabilities that protect Adobe, our products, and our customers. Our team sits where cybersecurity, large-scale data, and AI meet, building models for anomaly detection, threat detection, investigation, and security analytics across some of Adobe s largest datasets. As a Staff Machine Learning Engineer, you ll design, build, and scale production ML systems spanning deep learning, behavioral modeling, embeddings, and agentic AI. You ll write code, train models, run experiments, and help shape the architecture the broader team builds on. You ll also partner closely with data, platform, and security engineers across Adobe. The Challenge Architect end-to-end ML systems for high-volume security data, turning experiments into reusable capabilities. Own the ML lifecycle, from feature engineering through training, deployment, monitoring, and retraining. Build LLM and agentic AI capabilities for security investigation, including retrieval-augmented generation. Design evaluation frameworks that measure model quality and help analysts trust and validate results. Work with data and platform engineers to scale pipelines and resolve system bottlenecks together. Mentor engineers and help guide technical direction through design reviews and hands-on collaboration. What you bring Experience running production ML systems from early experimentation through sustained operation at scale. A strong background training models with PyTorch and transformers, including behavioral modeling and anomaly detection. Comfort with distributed compute like Spark, cloud platforms like AWS, and MLOps tools like MLflow. Experience building with LLMs or generative AI, along with evaluating how they behave in production. Strong Python and SQL skills, and solid software engineering habits like testing and code review. A collaborative approach to mentoring engineers and shaping technical direction across teams. MS or PhD in computer science, machine learning, or a related field, or equivalent practical experience. Nice to have Background applying ML to cybersecurity, fraud, or similar adversarial problems. Experience with vector databases, RAG, or multi-agent systems. Publications, patents, or open-source contributions to ML or AI. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000 employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience . Expected Pay Range: Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $172,500 - $306,625 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. In California, the pay range for this position is $211,800 - $306,625 At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC base commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP). In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award. State-Specific Notices: California : Fair Chance Ordinances Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. Colorado: Application Window Notice If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs. Massachusetts: Massachusetts Legal Notice It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Requirements

Must-haves

The Challenge Architect end-to-end ML systems for high-volume security data, turning experiments into reusable capabilities.
Own the ML lifecycle, from feature engineering through training, deployment, monitoring, and retraining.
Build LLM and agentic AI capabilities for security investigation, including retrieval-augmented generation.
Design evaluation frameworks that measure model quality and help analysts trust and validate results.
Work with data and platform engineers to scale pipelines and resolve system bottlenecks together.
Mentor engineers and help guide technical direction through design reviews and hands-on collaboration.
What you bring Experience running production ML systems from early experimentation through sustained operation at scale.
A strong background training models with PyTorch and transformers, including behavioral modeling and anomaly detection.
Comfort with distributed compute like Spark, cloud platforms like AWS, and MLOps tools like MLflow.
Experience building with LLMs or generative AI, along with evaluating how they behave in production.
Strong Python and SQL skills, and solid software engineering habits like testing and code review.
A collaborative approach to mentoring engineers and shaping technical direction across teams.
MS or PhD in computer science, machine learning, or a related field, or equivalent practical experience.
Experience with vector databases, RAG, or multi-agent systems.
Publications, patents, or open-source contributions to ML or AI.
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
Fair Chance Ordinances
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
Application Window Notice
Massachusetts Legal Notice

Nice-to-haves

Nice to have Background applying ML to cybersecurity, fraud, or similar adversarial problems.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlaimachine learningllmawspythonsql

Platform: workday
Effort: long