Machine Learning Engineer 5

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 you'll 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