Sr Machine Learning Engineer 5 -- AEP, Agentic System

Adobe • San Jose, CA

1d

About The Position

At Adobe’s Experience Platform, we are looking for a Senior Machine Learning Engineer to compose, build, and operate scalable intelligent AI systems that power end-user AI products. You will work closely with Adobe Research, product teams, and platform engineers to bring new capabilities from concept to production with strong reliability, governance, and measurable impact. This is a senior, hands-on role with significant architectural ownership across the agent stack: orchestration, tool integration, retrieval and memory services, evaluation, safety/guardrails, and high-performance backend systems . The work is fast-paced, collaborative, and deeply data-driven—balancing research innovation with real-world product constraints and customer value.

Requirements

• Graduate degree with 10+ years of experience, or PhD with 8+ years building and deploying ML systems at scale.
• Deep expertise in machine learning, end-to-end modeling life cycle, and real-time decisioning architectures.
• Some experience with LLMs, agentic systems, prompt engineering, RAG, or context engineering, especially in production environments.
• Proven success in building and shipping end-to-end ML systems, from research to deployment and ongoing optimization.
• Hands-on experience with MLOps, including model lifecycle management, monitoring, automated retraining, CI/CD for ML, and large-scale inference systems.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace, LangChain, or equivalent.
• Excellent multi-functional collaboration skills and demonstrated technical leadership.
• Experience bridging research and production in enterprise-scale AI applications.

Responsibilities

• Own end-to-end architecture and delivery of production-grade agentic AI systems—from orchestration and tool execution to retrieval and response generation—built for reliability, scale, and maintainability.
• Build AI-powered product capabilities using predictive and generative approaches, enabling autonomous agents that improve customer experience workflows.
• Design robust agent orchestration (single- and multi-agent), including planning, delegation, and structured tool use, with strong control flow and failure handling.
• Develop core platform components such as retrieval (RAG), memory/state, and LLM/provider abstraction, and drive ongoing improvements through evaluation, monitoring, and experimentation.
• Establish safety, governance, and ML Ops guidelines (guardrails, observability, CI/CD, operational readiness) to ensure trustworthy, production-quality outcomes.
• Partner with Adobe Research and multi-functional teams to translate prototypes into product-ready systems, making clear tradeoffs across quality, latency, cost, and risk.
• Provide technical leadership through design docs, reviews, mentoring, and cross-team alignment—raising the bar for agentic AI engineering.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees