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
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
Monitor and evaluate the performance of ML models, making vital adjustments to compete at the highest level
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 and statistics, including Bayesian Modeling, Time Series Analysis, Reinforcement Learning, and Optimization
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
Job Classification
Industry: IT Services & Consulting Functional Area / Department: Data Science & Analytics Role Category: Data Science & Machine Learning Role: Machine Learning Engineer Employement Type: Full time