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NEXTMOVEFDE careers · United States
Adobe

Machine Learning Engineer 5

AI summary of the role

Adobe Brand Intelligence Predict is building LLM-powered synthetic audiences that let brands pre-test ads and campaigns before spending.

What you’ll do

  • Design, build, and ship LLM-powered systems that simulate consumer audiences end-to-end, from proof-of-concept to production.
  • 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.

What you’ll bring

  • 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.

Technologies

LLM · PyTorch · Hugging Face · vLLM · W&B · AWS · GCP · Azure · RAG · RLHF

About Adobe

Builds creative, document, and enterprise customer-experience software, now embedding Firefly AI and agents across creator and marketer workflows.

Public · 5000+ people

Source and classification

Production engineering · Evidence for this classification:

Machine Learning Engineer — Brand Intelligence Predict The Opportunity Join us at Adobe as a Machine Learning Engineer (MLE 50) 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. What you'll Do Design, build, and ship LLM-powered systems that simulate consumer audiences end-to-end, from proof-of-concept to production. 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
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