Hiring: Senior Machine Learning Engineer Company: Adobe Location: San Jose, CA Job Posted Time: 2026-09-16 09:28:13 Target Skills & Keywords : AWS, Azure, Azure AD, Deep Learning, Elasticsearch, Express, Fine-tuning, HTML, Java, LLM, Make, Microservices, Move, PostgreSQL, PyTorch, Python, RAG, Redis, Snowflake, TensorFlow About the job Experience: •5+ years of experience building and deploying production ML systems, with demonstrated work on models and AI-powered applications that serve real users at scale. Required Skills: •Build the Agent Platform That Powers Enterprise AI •The team is growing fast to match the scale of what we’re building — we’re actively hiring multiple Senior ML Engineers across the focus areas described below. We’ll match your strengths to the right domain during the interview process. •You'll spend most of your time building platform infrastructure, with regular exposure to customer needs that shapes what you build. •Build core agent infrastructure. Own major components of the platform — the agent runtime, tool execution layer, memory systems, sandboxed execution, or control plane — and ship production-ready code against real constraints: sub-second orchestration latency, cost-aware model routing, and high-throughput inference pipelines. •Design ML workflows at enterprise scale. Build the systems for model customization, serving, and lifecycle management that let the platform adapt to diverse customer workloads. •Innovate, don't just build. You'll have room to explore new approaches to agent reasoning, tool orchestration, memory, or evaluation — and carry the best ideas from experiment to production. We value engineers who push the platform forward with original thinking, not just execute on a spec. •Close the loop with customers. Join regular customer engagements to see how your systems perform in real deployments, then feed those insights back into the platform roadmap. This isn't a customer-facing role, but your work is directly shaped by the people who use it. •Own what you ship. Architecture through production operations — deployment, monitoring, observability, and incident response. No throwing code over the wall. Qualifications: •Ph.D. or M.S. in Computer Science or related field required. •5+ years of experience building and deploying production ML systems, with demonstrated work on models and AI-powered applications that serve real users at scale. •Strong software engineering fundamentals: proficiency in Python and/or Java, experience designing APIs and microservices, and comfort owning production systems end-to-end (deployment, monitoring, incident response). •Deep hands-on experience with at least one modern deep learning framework (PyTorch, TensorFlow, JAX). •Production experience with LLMs: prompt/context engineering, working with LLM APIs, fine-tuning, or building LLM-powered applications. •Practical experience utilizing cloud platforms (AWS or Azure) and data infrastructure (Postgres, Redis, Elasticsearch, Snowflake, or similar). •Self-motivated with strong communication skills and the ability to influence technical decisions in a collaborative, multi-functional environment. •You don't need all of these — depth in one or two is what matters. We'll match you to the domain where your experience has the most impact. •Agent or LLM infrastructure depth. You've built agent loops, tool-use orchestration, RAG pipelines, long-term memory systems, or fine-tuning/serving infrastructure — not as a prototype, but in production systems handling real traffic. •Platform-scale systems thinking. You've designed catalog systems, plugin architectures, or intent routing that work across hundreds or thousands of endpoints, and you've dealt with the messy reality of overlap resolution, versioning, and cost-aware routing at that scale. Compensation: •$151,800 - $265,350 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!