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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer 5 - **Company:** Adobe Inc. - **Location:** San Jose, CA, United States (Remote available) - **Salary:** $211,800.0 - $306,625.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Structures, Python (Programming Language), Machine Learning, Azure Machine Learning, Google Cloud, Pytorch, Large Language Models, Adobe, Information Technology, HuggingFace, Machine Learning Operations - **Published:** August 24, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/peciej5wqv ## About the Role * 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. ## Description 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 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. ## Related Videos - [3x Performance: A Humbling Journey](https://www.wearedevelopers.com/videos/100165-3x-performance-a-humbling-journey) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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