Adobe—Senior Machine Learning Engineer 5

Job description

Description: We are looking for a Senior ML Engineer to lead foundational research in agentic AI and intelligent systems. This is a research-intensive role focused on advancing the underlying models, learning paradigms, and capabilities that enable AI agents to reason, plan, learn, remember, interact with tools, and operate effectively over complex, long-horizon tasks. This is not a prompt-engineering or agent orchestration role. We are looking for a scientist with strong fundamentals in machine learning and deep learning who can develop novel modeling and learning approaches, rather than primarily assembling existing LLMs, prompts, or agent frameworks. The ideal candidate will have deep expertise in one or more areas of generative modeling, large language models, NLP, computer vision, multimodal learning, representation learning, reinforcement learning, or related areas, along with the ability to connect these foundations to emerging agentic systems. The role will involve identifying fundamental research problems in agentic intelligence, developing new algorithms and model architectures, designing rigorous experiments, and translating research advances into product. Key Responsibilities - Conduct fundamental and applied research in agentic AI, foundation models, reasoning, planning, memory, tool use, multimodal intelligence, and long-horizon interaction. - Develop novel model architectures, learning algorithms, training methodologies, and inference techniques to improve the capabilities of AI agents. - Advance the underlying intelligence of agents through research in LLMs, generative models, NLP, computer vision, multimodal learning, representation learning, and reinforcement learning. - Investigate problems such as reasoning, planning, memory, grounding, adaptation, self-improvement, tool use, and learning from interaction. - Build and evaluate research prototypes and establish rigorous experimental methodologies to validate new ideas. - Rigorous experimentation to take the final solution to product, submit IP and publish at top-tier conferences. - Stay at the forefront of rapidly evolving research in foundation models and agentic AI, identifying opportunities where fundamental advances can create differentiated product capabilities. Leadership & Collaboration - Lead technical design reviews, write engineering RFCs, and set quality standards for the team. - Mentor junior and mid-level ML engineers through code reviews, 1:1s, and pair-programming sessions. - Collaborate with product, research, and infrastructure teams to translate research ideas into shipped features. Required Qualifications - 9+ years of hands-on ML engineering experience in industry or research. - MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field, with significant industry or research experience. - Strong fundamentals in machine learning, deep learning, optimization, and statistical modeling. - Demonstrated research experience in one or more of: - Large Language Models and NLP - Generative modeling (diffusion, flow matching, autoregressive models, VAEs, etc.) - Computer Vision - Multimodal foundation models - Representation learning - Reinforcement learning / learning from interaction - Reasoning and planning - Demonstrated ability to formulate novel research problems, develop new approaches, and experimentally validate hypotheses. - Strong publication record and/or demonstrated track record of delivering novel ML research with measurable impact. - Strong programming and experimentation skills, particularly with modern deep learning frameworks - Excellent written and verbal communication skills with cross-functional stakeholders. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create. 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 protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process 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. AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. 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. Skills: machine learning, deep learning, large language models, natural language processing, generative modeling, computer vision, multimodal learning, representation learning, reinforcement learning, optimization, statistical modeling, model architecture design, algorithm development, experimental design, research prototyping, technical documentation, mentoring, cross-functional collaboration, code review, product development, ip submission, conference publication