Machine Learning Engineer 5
Role details
Job location
Tech stack
Job 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.
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 - you have opinions about what makes an eval load-bearing versus theater.
- 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 or equivalent experience in Computer Science, Machine Learning, or a related technical field, or equivalent experienc
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.
Benefits & conditions
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 $172,500 -- $306,625 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 $211,800 - $306,625
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.