Senior Manager, Machine Learning Engineering

The Opportunity

At Adobe, we are applying cutting-edge AI to reimagine document experiences and transform knowledge work. We are looking for an exceptional engineering leader to build and lead this team. You will set the technical direction, grow a group of strong ML and software engineers, and turn ambitious, ambiguous ideas into products customers use and trust. This is a high visibility role, with real ownership, and the chance to shape how agentic AI shows up across Adobe's document products.

What You'll Do

• Define a multi-horizon strategy for our agentic, memory, and retrieval capabilities, grounded in what is possible now and what is coming.
• Partner with Product Management to shape the roadmap, communicate what is feasible today and in the near future, and translate customer problems into well-scoped, measurable projects.
• Act as a bridge between Adobe's research labs, product, design, and engineering teams so that efforts are aligned and amplified, and incubated work transitions smoothly to production.
• Hire, develop, and retain a diverse team of engineers and ML practitioners. Set clear expectations, give candid feedback, and create growth paths for senior and early-career engineers alike.
• Own the full lifecycle of ML product development: system design, data and ML pipelines, evaluation, productization, and MLOps.
• Establish rigorous evaluation practices for agent, memory, and retrieval quality, including benchmarks, LLM-as-a-judge approaches, offline and online metrics, and regression testing.
• Build a culture of disciplined engineering and fast experimentation, with deep engagement with customers and a bias toward measurable impact.
• Manage scope, risk, and delivery using data, analytics, and creative problem solving. Promote responsible AI, security, privacy, and cost-aware design.

Required Qualifications

• 10+ years of experience applying modern AI/ML techniques to build ML features or products, including technical leadership of teams and projects.
• 6+ years of people management experience
• Hands-on experience managing engineers or ML practitioners, including hiring, performance management, and career development.
• Experience delivering ML or GenAI systems from 0->1 through production and ongoing iteration.
• Strong technical foundation in machine learning, software engineering, and distributed systems, sufficient to guide architecture decisions and review designs with senior engineers.
• Familiarity with LLM-based applications, including retrieval-augmented generation, agentic architectures, and evaluation of generative systems.
• Track record of delivering high-quality, cloud-scale, data-driven products that are widely adopted by large customer bases.
• Demonstrated ability to influence technical and non-technical stakeholders, and to lead effectively in a high-growth, matrixed organization.
• An ability to think strategically, look around corners, and create a vision for the current quarter, the year, and five years down the road.
• A relentless pursuit of great customer experiences and continuous improvements to the product."
• Master's or Ph.D. in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience building or managing teams working on memory systems, retrieval and search infrastructure, or agent frameworks.
• Experience with LLM evaluation methodologies, prompt optimization, and observability for LLM and agent workflows.
• Experience with MLOps tooling, experiment tracking, and model lifecycle management on AWS, GCP, or Azure.
• Experience running incubation or zero-to-one teams, including taking early prototypes through to scaled product adoption.
• Track record of collaborating with research organizations and translating research into product.
• Experience in document, productivity, or knowledge-work products.

AI Use Guidelines for Interviews

Our interviews are designed to reflect your own skills and thinking. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

At Adobe, we empower employees to innovate with AI - and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it's restricted during live interviews. See how we think about AI in the hiring experience.

Expected Pay Range

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 $178,900 - $351,225 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. In Washington, the pay range for this position is $215,600 - $312,200

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.