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# Machine Learning Engineer

- **Company:** Adobe Systems
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $238,700.0 - $345,650.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Automated Storage and Retrieval Systems, Microsoft Azure, Databases, Distributed Systems, Python (Programming Language), Machine Learning, NoSQL, Open Source Technology, Tensorflow, Software Engineering, SQL Databases, AI Infrastructure, Reinforcement Learning, Data Logging, Pytorch, Large Language Models, Multi-Agent Systems, Backend, Event Driven Architecture, Adobe, Containerization, Kubernetes, Information Technology, HuggingFace, Machine Learning Operations, Virtual Agents, Api Design, Data Pipelines, Docker, Microservices
- **Published:** August 19, 2026
- **Apply:** https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Machine-Learning-Engineer_R171337

## About the Role

We are looking for a Staff Backend Engineer with 10+ years of experience in enterprise software development using Machine Learning and Agentic AI systems to help design and scale the infrastructure behind intelligent, autonomous applications. You'll work at the intersection of backend engineering, applied ML, and AI agent orchestration. Your role includes building APIs, data pipelines, and runtime frameworks for intelligent workflows., * BA/BS or MS degree in Computer Science, Engineering, or equivalent experience.

 * Strong backend engineering skills with Python

 * Proficiency in Agentic AI development

 * Proficiency in building APIs, distributed systems, and data pipelines.

 * Hands-on experience with LLMs, vector databases (Pinecone, Weaviate, FAISS, Milvus), and ML deployment frameworks.

 * Understanding of agentic AI concepts (tool calling, memory, planning, reasoning).

 * Familiarity with ML frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex.

 * Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes).

 * Solid knowledge of databases (SQL and NoSQL) and event-driven architectures.

Nice to Have

 * Familiarity with LangGraph, AutoGen, or other agentic frameworks.

 * Contributions to open-source ML or AI infrastructure projects.

 * Exposure to MLOps tooling (MLflow, Weights & Biases, Ray, Prefect, Airflow).

 * Background in security for AI systems (guardrails, prompt injection defense, data privacy).

 * Experience with reinforcement learning, multi-agent systems, or fine-tuning LLMs.

About Adobe

## Description

* Architect, implement, and scale backend services that support AI applications powered by machine learning and autonomous agents.

 * Design APIs and microservices that integrate LLMs, vector databases, and knowledge retrieval systems.

 * Build infrastructure for AI agents (task planning, tool use, orchestration, state management).

 * Ensure backend systems are reliable, performant, and secure at scale.

 * Develop monitoring, logging, and observability for agent behaviors and ML pipelines.

 * Work closely with product and design teams to translate requirements into scalable backend solutions.

 * Stay ahead of with emerging research in LLMs, multi-agent systems, and autonomous AI.

What is needed to Succeed


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