Adobe Inc.
Our Company
Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging artists to global brands-everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!
Senior Machine Learning Engineer - Agentic AI & Semantic Intelligence Job Description Summary Core Focus: Develops modern agentic AI systems, reinforcement learning algorithms for autonomous agents, and sophisticated semantic search solutions. Builds full-stack ML systems from research prototypes to production deployment, combining deep learning, reinforcement learning, and semantic understanding technologies.
Key Responsibilities: Architects and develop agentic AI systems that autonomously create and manage audiences, implements RL frameworks for agent decision-making, and builds semantic search engines with advanced intent classification. Creates end-to-end solutions from algorithm implementation to API design.
The Opportunity Join Adobe's mission to revolutionize marketing automation through Agentic AI and Semantic Intelligence. We're building next-generation AI agents that autonomously understand marketer and user intent, make intelligent decisions about audience creation, and deliver personalized experiences through advanced semantic understanding.
As a Senior Machine Learning Engineer specializing in Agentic AI and Reinforcement Learning, you'll be the technical architect behind our autonomous audience agents, developing sophisticated RL algorithms and semantic search systems that seamlessly integrate these capabilities.
What You'll Do Agentic AI & Reinforcement Learning
Design and implement RL frameworks for autonomous audience agents using advanced algorithms (PPO, A3C, SAC)
Develop multi-agent systems for collaborative audience creation and management tasks
Build reward functions and training environments that learn from real marketing outcomes
Architect agent systems (reactive, deliberative, hybrid) for real-world applications
Semantic Search & Intent Understanding
Build semantic search engines using transformer models, vector databases, and dense retrieval systems
Develop intent classification models that translate marketing queries into actionable audience definitions
Create embedding pipelines for real-time semantic matching between user profiles and objectives
Implement cross-encoder re-ranking systems for improved search relevance
Full-Stack Development & Research
Design end-to-end ML pipelines from data ingestion through model serving, monitoring and retraining
Build scalable APIs and microservices supporting real-time agent decision-making
Stay at the forefront of agentic AI research, implementing modern techniques from academic literature
Conduct applied research on novel RL formulations and semantic understanding techniques
What You Need to Succeed Educational Requirements
Ph.D. in AI, ML, Computer Science, or related field with 2+ years of agentic AI/RL experience, OR
Master's degree with 5+ years building production ML systems focused on autonomous agents and semantic search
Core Technical Skills Agentic AI & Reinforcement Learning
Expert experience with RL frameworks (Ray RLlib, Stable-Baselines3, OpenAI Gym)
Deep understanding of RL algorithms: policy gradients, actor-critic methods, multi-agent RL
Hands-on experience building autonomous agents for real-world applications
Semantic Search & NLP
Advanced expertise in transformer architectures, embedding models, and vector search
Production experience with semantic search systems (FAISS, Milvus, similar vector DBs)
Strong background in intent classification, BERT/sentence transformers, cross-encoder architectures
Full-Stack Development
Expert Python programming with proficiency in Go, or Rust, or Java
Production ML experience with PyTorch/JAX, training, finetuning and model deployment
System design expertise for high-scale, low-latency ML serving infrastructure
Database proficiency (PostgreSQL, vector databases)
Infrastructure & Operations
Large-scale data processing (Spark, Kafka, distributed computing)
Cloud platform expertise (AWS, GCP, Azure) with ML services
MLOps capabilities: CI/CD, model monitoring, A/B testing frameworks
API development and microservices architecture
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 $162,000 – $301,200 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.
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.
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 applicable characteristics protected by law. Learn more.
Adobe aims to make Adobe.com 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 or call (408) 536-3015.
#J-18808-Ljbffr
We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!
Senior Machine Learning Engineer - Agentic AI & Semantic Intelligence Job Description Summary Core Focus: Develops modern agentic AI systems, reinforcement learning algorithms for autonomous agents, and sophisticated semantic search solutions. Builds full-stack ML systems from research prototypes to production deployment, combining deep learning, reinforcement learning, and semantic understanding technologies.
Key Responsibilities: Architects and develop agentic AI systems that autonomously create and manage audiences, implements RL frameworks for agent decision-making, and builds semantic search engines with advanced intent classification. Creates end-to-end solutions from algorithm implementation to API design.
The Opportunity Join Adobe's mission to revolutionize marketing automation through Agentic AI and Semantic Intelligence. We're building next-generation AI agents that autonomously understand marketer and user intent, make intelligent decisions about audience creation, and deliver personalized experiences through advanced semantic understanding.
As a Senior Machine Learning Engineer specializing in Agentic AI and Reinforcement Learning, you'll be the technical architect behind our autonomous audience agents, developing sophisticated RL algorithms and semantic search systems that seamlessly integrate these capabilities.
What You'll Do Agentic AI & Reinforcement Learning
Design and implement RL frameworks for autonomous audience agents using advanced algorithms (PPO, A3C, SAC)
Develop multi-agent systems for collaborative audience creation and management tasks
Build reward functions and training environments that learn from real marketing outcomes
Architect agent systems (reactive, deliberative, hybrid) for real-world applications
Semantic Search & Intent Understanding
Build semantic search engines using transformer models, vector databases, and dense retrieval systems
Develop intent classification models that translate marketing queries into actionable audience definitions
Create embedding pipelines for real-time semantic matching between user profiles and objectives
Implement cross-encoder re-ranking systems for improved search relevance
Full-Stack Development & Research
Design end-to-end ML pipelines from data ingestion through model serving, monitoring and retraining
Build scalable APIs and microservices supporting real-time agent decision-making
Stay at the forefront of agentic AI research, implementing modern techniques from academic literature
Conduct applied research on novel RL formulations and semantic understanding techniques
What You Need to Succeed Educational Requirements
Ph.D. in AI, ML, Computer Science, or related field with 2+ years of agentic AI/RL experience, OR
Master's degree with 5+ years building production ML systems focused on autonomous agents and semantic search
Core Technical Skills Agentic AI & Reinforcement Learning
Expert experience with RL frameworks (Ray RLlib, Stable-Baselines3, OpenAI Gym)
Deep understanding of RL algorithms: policy gradients, actor-critic methods, multi-agent RL
Hands-on experience building autonomous agents for real-world applications
Semantic Search & NLP
Advanced expertise in transformer architectures, embedding models, and vector search
Production experience with semantic search systems (FAISS, Milvus, similar vector DBs)
Strong background in intent classification, BERT/sentence transformers, cross-encoder architectures
Full-Stack Development
Expert Python programming with proficiency in Go, or Rust, or Java
Production ML experience with PyTorch/JAX, training, finetuning and model deployment
System design expertise for high-scale, low-latency ML serving infrastructure
Database proficiency (PostgreSQL, vector databases)
Infrastructure & Operations
Large-scale data processing (Spark, Kafka, distributed computing)
Cloud platform expertise (AWS, GCP, Azure) with ML services
MLOps capabilities: CI/CD, model monitoring, A/B testing frameworks
API development and microservices architecture
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 $162,000 – $301,200 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.
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.
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 applicable characteristics protected by law. Learn more.
Adobe aims to make Adobe.com 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 or call (408) 536-3015.
#J-18808-Ljbffr