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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying multimodal and generative AI systems, with a strong focus on machine learning lifecycle management and technical leadership. Proficient in building scalable APIs and integrating AI capabilities into production environments.
Highest-signal resume keywords
Machine Learning Systems DeploymentGenerative AI ExpertiseTransformers and Diffusion ModelsPython and PyTorch ProficiencyTechnical Leadership and Mentoring
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningComputer VisionAgentic AI SystemsModel EvaluationData StructuresAlgorithmsTestingCode QualityAPI DesignDistributed Services
Soft Skills
CollaborationProblem SolvingMentoring
Tools & Technologies
AWSAzureDockerKubernetesChatGPTClaudeCursor
Certifications & Qualifications
MS or PhD in Computer ScienceMachine Learning
Industry Keywords
Generative AIMultimodal Machine LearningCreative Cloud WorkflowsAI Evaluation and SafetyAgent Frameworks
Tech Stack
Tools & technologiesAWSAzureCloudDockerKubernetesPythonPyTorch
About the role
Key responsibilities & impact- Lead the design, development, and deployment of multimodal and generative AI systems spanning vision, language, and other modalities
- Build and productionize transformers, diffusion models, LLMs, and vision-language models for content creation, understanding, and transformation
- Develop agentic AI systems that reason, use tools, interact with models and services, and complete complex multi-step creative workflows
- Build intelligent capabilities for Firefly AI Assistant and Creative Cloud workflows
- Develop scalable services and APIs integrating AI and machine learning into Adobe products
- Drive the end-to-end ML lifecycle, including problem formulation, modeling, experimentation, evaluation, deployment, monitoring, and iteration
- Partner with engineering, product, design, and research teams to translate customer needs into ML solutions
- Improve performance, scalability, reliability, and quality of AI systems in high-traffic production environments
- Provide technical leadership and mentor engineers
- Identify opportunities to apply generative and agentic AI to challenges for creative professionals and enterprise customers
Requirements
What you’ll need- 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
- Hands-on experience with transformers, diffusion models, LLMs, or VLMs
- Solid foundation in probability, statistics, machine learning, and model evaluation
- Proficiency in Python and machine learning frameworks such as PyTorch
- Experience designing and building scalable APIs, distributed services, or production ML infrastructure
- Strong software engineering fundamentals, including data structures, algorithms, testing, code quality, and code reviews
- Experience with AWS or Azure
- Experience with Docker and Kubernetes
- Familiarity with AI-assisted development tools such as ChatGPT, Claude, Cursor, or similar tools
- Nice-to-have experience with production agentic AI platforms or multi-agent systems, multimodal learning, video understanding or generation, foundation model optimization, AI evaluation and safety, agent frameworks, retrieval systems, creative applications, research, or open-source projects
Benefits
Comp & perks- Annual Incentive Plan (AIP) for non-sales roles
- Potential long-term incentives in the form of a new hire equity award for eligible roles
- Comprehensive benefits programs
- Reasonable accommodations during the recruiting process
- Equal Employment Opportunity protections