Adobe Advertising is a combination of a Demand Side Platform (DSP) and a Spend Optimizer that helps customers plan, buy, measure, and optimize their digital media (across CTV, Online Video, Display, Search, Social, and Retail Media Networks). We help the largest global advertisers maximize the impact of their paid media budgets by delivering connected and personalized experiences to their consumers.
The Opportunity
This opportunity is with the Spend Optimizer group. In collaboration with a team of highly motivated data scientists and engineers, you will apply reinforcement learning, time series analysis, bayesian modeling, Gen AI frameworks to optimize ad spends.
What youll Do
Identify and develop the next generation of experiences for Ad Cloud customers
Be hands on with up coming AI Technology and guide the development of the product roadmap
Technically lead and guide team of skilled machine learning engineers to design and implement ML algorithms/models
Collaborate with multi-functional teams to determine technical requirements
Develop and deploy scalable machine learning solutions that optimize Adobe s products and services, deliver value to clients and drive customer adoption
Drive innovation through research and experimentation, encouraging an environment where new ideas can thrive
What you need to succeed
Outstanding knowledge of machine learning frameworks and tools such as PyTorch, Tensorflow, Scikit-learn, with strong programming skills in Python
Solid understanding of core machine learning, statistics and AI, including Bayesian Modeling, Time Series Analysis, Reinforcement Learning, Optimization, Deep Learning, Information Retrieval and RAG, Agentic Systems and LLM use cases. Ability to communicate technical outcomes to a non-Data Science audience will be a plus
Experience in developing, deploying and maintaining ML models in a production environment
Ability to thrive in a collaborative, inclusive, and diverse workplace, embracing different perspectives and ideas
Ideal Candidate Profile:
A total of 10+ years of experience in an applied Machine Learning setting, delivering cloud-scale, data-driven products, and services
PhD or Master s in Computer Science/ Applied Math/Statistics/ related field.
Experience and domain expertise in Digital Ad Technologies is desirable.
Comfort with ambiguity, adaptability to evolving priorities, and an ability to influence technical and non-technical collaborators
Strong problem solving skills, ability to learn fast, extreme design and implementation skills can compensate for any of the above requirements
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Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full time