Staff Machine Learning Engineer

Adobe’s Brand AI Services team is hiring a Staff Machine Learning Engineer to build production-grade multimodal and agentic generative AI for Firefly AI Assistant and Creative Cloud workflows.

Responsibilities

• Lead end-to-end design, development, and deployment of multimodal and generative AI systems across vision, language, and other modalities
• Build and productionize generative AI models and systems, including transformers, diffusion models, LLMs, and vision-language models (VLMs) for content creation, understanding, and transformation
• Develop agentic AI systems capable of reasoning, tool use, model and service interaction, and completing complex multi-step creative workflows
• Create intelligent capabilities for Firefly AI Assistant and Creative Cloud workflows to support creative professionals from intent and ideas to high-quality outcomes
• Develop scalable services and APIs that embed AI and machine learning capabilities into Adobe products
• Own the ML lifecycle: problem formulation, modeling, experimentation, evaluation, deployment, monitoring, and iteration
• Partner with engineering, product, design, and research teams to translate customer needs into effective ML solutions
• Improve performance, scalability, reliability, and quality of AI systems in high-traffic production environments
• Provide technical leadership, mentor engineers, and help raise the engineering and machine learning bar across the team
• Identify opportunities to apply generative and agentic AI to real-world challenges for creative professionals and enterprise customers

Requirements

• MS or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience
• 5+ years of experience building and deploying machine learning systems in production
• Hands-on experience designing and building agentic AI systems, including tool use, agent orchestration, multi-step workflows, planning and reasoning, retrieval, memory, or human-in-the-loop systems
• Experience with agent interoperability and tool integration, including Model Context Protocol (MCP), function/tool calling, or similar frameworks and protocols
• Expertise in computer vision, generative AI, and/or multimodal machine learning, with hands-on experience using transformers, diffusion models, LLMs, or VLMs
• Strong foundation in probability, statistics, machine learning, and model evaluation
• Proficiency in Python and experience with machine learning frameworks such as PyTorch
• Experience designing and building scalable APIs, distributed services, or production ML infrastructure
• Strong software engineering fundamentals: data structures, algorithms, testing, code quality, and code reviews
• Experience with cloud platforms such as AWS or Azure plus containerization and orchestration technologies such as Docker and Kubernetes
• Familiarity with modern AI-assisted development tools and workflows, including ChatGPT, Claude, Cursor, or similar tools, for development, experimentation, or productivity

Technologies

• Python, PyTorch
• Transformers, diffusion models, LLMs, VLMs
• Model Context Protocol (MCP), function/tool calling
• AWS, Azure
• Docker, Kubernetes
• ChatGPT, Claude, Cursor

Nice to Have

• Experience building production agentic AI platforms or multi-agent systems, including agent evaluation, observability, reliability, or safety
• Experience with multimodal learning across video, audio, or 3D data
• Background in video understanding or generation, temporal modeling, or streaming ML systems
• Experience fine-tuning, adapting, or optimizing large-scale foundation models
• Knowledge of AI evaluation, safety, and responsible AI practices
• Experience with agent frameworks, orchestration platforms, retrieval systems, or enterprise knowledge integration
• Experience building AI-powered tools or workflows for creative professionals, content creation, or creative applications
• Contributions to research, open-source projects, or applied machine learning innovation

Interview AI Use Guidelines

• 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

Pay

• U.S. pay range: $172,500 - $306,625 per year
• California pay range: $211,800 - $306,625 per year

Location: San Jose, CA (onsite)