Principal Machine Learning Engineer

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone from emerging artists to global brands everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.

We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity

The Adobe Experience Platform (AEP) Architecture team is looking for a Principal Scientist, Machine Learning to help us both architect and build new intelligent features for our platform.

You will join a group of Architects and Principal Scientists who are working to invent the future of customer experience software.

Help create a platform that lets the world's leading brands engage in a hyper-personalized way with their customers.

What you'll Do

• Collaborate with the Product Management, Engineering and Research teams to select, implement, curate, and continuously improve AI / ML models for our enterprise SaaS platform
• Use your expertise in Statistical Sciences and AI / ML to help build our new Knowledge Assistant, predictive models and experimentation frameworks
• Build systems and practices for rapidly taking data science and ML from research to customer feature with the highest quality and safety · Partner with Adobe Research to develop, refine and iteratively improve groundbreaking AI models
• Participate in our Architecture Review Board to assure we design our software to the exacting standards of Adobe and our customers
• Mentor individual contributors within the Adobe engineering and architecture organization

What you need to succeed

• An MS or PhD degree in an analytical field such as : Statistics, Physics, Computer Science, Applied Mathematics etc. or equivalent experience
• At least 10 years of experience in data science, AI / ML engineering or related role
• Solid understanding of Statistical Learning Models (Regression, Classification, Tree Based Models, SVM, Neural Networks, Clustering, Time Series, Anomaly Detection).
• Must have an excellent grasp of statistical inference methods (both Bayesian and Frequentist), in particular as related to hypothesis testing, including : experience with power and sample-size calculations, multiple hypothesis testing, non-parametric tests, and multi-arm bandits.
• Knowledge of generative AI and LLMs a plus
• Expertise with one or more machine learning, deep learning, or statistical modeling tools such as R, scikit-learn, and JupyterLab.
• Understanding of software architecture and database design, particularly in a large enterprise SaaS environment · Demonstrated record in shipping customer facing AI / ML powered applications at scale
• Skilled in use of Python, SQL, Spark or other data management / manipulation tools · Passion for coaching and mentoring software developers and machine learning engineers.

Our compensation reflects the cost of labor across several geographic markets, and we pay differently based on those defined markets.

The pay range for this position is $189,400 $357,900 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.

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.