Senior Applied Scientist

Description

Senior Applied Scientist — Brand Intelligence Predict

The Opportunity

Join us at Adobe as a Senior Applied Scientist 5 on the Adobe Brand Intelligence Predict team in San Jose, CA! Help us build the next generation of synthetic audiences, LLM-powered simulated consumers that let the world's biggest brands pre-test ads, campaigns, and content before a single dollar is spent.

Adobe Brand Intelligence Predict is reinventing how brands make marketing decisions. Today, brands launch campaigns and wait weeks for the market to tell them what worked. Predict changes that — by simulating audiences of LLM-powered synthetic consumers, brands can pre-test creative, messaging, and product concepts in minutes against statistically grounded models of their real customers.

We sit at the frontier of one of the most actively-evolving areas in applied AI. The synthetic audiences research field has moved from "what if we asked GPT to play the ultimatum game?" in 2022 to competing paradigms — prompt-based persona binding, supervised fine-tuning on survey distributions, and RL-based latent state alignment — in 2026. No one has won yet. Our mission is to bring that science into product, and to do it at the speed and quality bar of a startup inside the company whose products every brand on Earth already uses.

About Adobe

Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.

Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.

Let’s Adobe together

At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.

Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com .

AI Use Guidelines for Interviews:

At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .

Expected Pay Range:

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.&xa;&xa;In California, the pay range for this position is $216,400 - $313,300&xa;

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.

State-Specific Notices:

California :

Fair Chance Ordinances

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

Colorado:

Application Window Notice

If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.

Massachusetts:

Massachusetts Legal Notice

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Responsibilities

• Invent, build, and ship LLM-powered systems that simulate consumer audiences end-to-end, advancing from initial validation to full deployment.
• Develop complex inference and reasoning harnesses on top of frontier LLMs, agentic flows, persona conditioning, retrieval, and sampling strategies tuned for distributional fidelity.
• Fine-tune LLMs on survey, panel, and behavioral data to improve alignment with real-world audience distributions; own the full loop from data curation through eval.
• Build the evaluation datasets, benchmarks, and harnesses that define what "good" means for synthetic audience quality - distributional fidelity, behavioral validity, subgroup calibration.
• Partner with product management, applied science, and engineering to translate a fast-moving research literature into shipping product features.
• What you need to succeed
• Substantial hands-on experience building LLM-based applications in production.
• Demonstrated experience designing and shipping complex inference harnesses on top of large language models (agentic systems, structured reasoning, sampling/decoding strategies, RAG).
• Hands-on experience fine-tuning LLMs with techniques including SFT, preference optimization (DPO/GRPO) and modern post-training tradeoffs.
• Experience with RLHF, RLAIF, or RL-based state alignment of LLMs.
• Proven track record of building evaluation datasets and harnesses.
• Proficiency in Python and strong grounding in data structures, algorithms, and modern ML tooling (PyTorch, Hugging Face, vLLM, W&B or equivalents).
• Hands-on knowledge of MLOps practices and pipelines.
• Familiarity with cloud ML services (AWS, GCP, Azure).
• Shipped a customer-facing Gen AI feature from proof-of-concept to production end-to-end.
• MS or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent experience.

Requirements

• Prior work on synthetic audiences, persona simulation, or LLM-based human behavior modeling.
• Familiarity with the synthetic audiences research literature (e.g., silicon samples, generative agents, SubPOP, HumanLM, DeepBind).
• Experience with public opinion or survey data (GSS, ANES, WVS, MIDUS) or panel-based consumer research data.