Senior Applied Scientist

Join us at Adobe as a Senior Applied Scientist on the Brand Intelligence Predict team in San Jose, CA. Help 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.

About the Role

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, enabling brands to 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 early experiments in 2022 to competing paradigms—prompt-based persona binding, supervised fine-tuning on survey distributions, and RL-based latent state alignment—in 2026. Our mission is to bring that science into product at the speed and quality bar of a startup inside Adobe.

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, including 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 evaluation.
• Build evaluation datasets, benchmarks, and harnesses that define what "good" means for synthetic audience quality—distributional fidelity, behavioral validity, and subgroup calibration.
• Partner with product management, applied science, and engineering to translate a fast-moving research literature into shipping product features.

Requirements

• 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.

Nice to Have

• 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.

About Adobe

Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity, and personalized customer experiences. Our 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. With over 30,000 employees worldwide, we’re on a mission to hire the very best and foster a culture where all employees are empowered to make an impact.

Pay

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