Applied Scientist

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!

At Adobe, we offer an outstanding opportunity for a Staff Applied Scientist to join our highly dedicated team in San Jose. In this world‑class role, you will:

• Identify business needs and transform them into statistical problems.
• Collect and cleanse large amounts of real‑world customer usage and commerce data in various product environments.
• Build predictive models from extensive datasets to solve business problems using sophisticated statistical analysis, machine learning, or data mining methods.
• Deliver informative and effective findings, results, and recommendations from machine learning models to collaborators, and build dashboards of key statistics and metrics.
• Leverage Large Language Models (LLMs) and develop AI Agents/Tools to enhance Adobe's business.
• Integrate LLM‑based solutions into Adobe workflows, ensuring scalability, performance, and compliance.

We are looking for ambitious and driven individuals with:

• A PhD or MS degree in Computer Science, Statistics, Electrical Engineering, Applied Math, Operations Research, Econometrics, or related fields.
• Strong expertise in statistical modeling, machine learning, deep learning, or data mining concepts, supported by a history of effectively resolving issues through these approaches.
• Proficiency in one or more programming languages such as Python, Java, Scala, and
  
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• Familiarity with machine learning or statistical modeling tools such as R, scikit‑learn, and Spark MLlib.
• Hands‑on experience with LLM frameworks and GenAI application development.
• Understanding of prompt engineering, model fine‑tuning, and evaluation techniques for LLMs.
• Strong analytical and quantitative problem‑solving skills.
• Excellent communication and relationship skills, and a strong team‑player attitude.

• Experience with big data techniques (such as Hadoop, Map Reduce, Hive, Pig, Spark).
• 4+ years of experience in machine learning, data mining, information retrieval, or statistical analysis.
• Knowledge of cloud platforms (such as AWS or Azure) and experience developing applications on these platforms using various cloud services.
• Experience with Econometric models.
• Experience deploying LLM‑based solutions in production environments, including optimization for latency and cost.

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $164,000 — $313,300 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.

In California, the pay range for this position is $216,400 — $313,300. 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.

Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

If this role is open to hiring in Colorado (as listed on the job posting),…