Senior Applied Scientist

What you'll do

• Build and ship LLM-powered systems to simulate consumer audiences for pre-testing marketing content.
• Develop complex inference and reasoning harnesses using agentic flows, persona conditioning, and retrieval strategies.
• Fine-tune LLMs on survey and behavioral data to align models with real-world audience distributions.
• Create evaluation datasets and benchmarks to measure distributional fidelity and behavioral validity of synthetic audiences.
• Translate research literature into functional product features in collaboration with product and engineering teams.
• Manage the full development lifecycle from initial data curation and validation to production deployment.

What we're looking for

• MS or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent experience.
• Substantial hands-on experience building LLM-based applications in production.
• Demonstrated experience designing and shipping complex inference harnesses including agentic systems, structured reasoning, and RAG.
• Hands-on experience fine-tuning LLMs using SFT, preference optimization (DPO/GRPO), and RLHF or RLAIF techniques.
• Proven track record of building evaluation datasets and harnesses for model performance.
• Proficiency in Python and strong grounding in data structures, algorithms, and modern ML tools like PyTorch and Hugging Face.
• Hands-on knowledge of MLOps practices, pipelines, and cloud ML services such as AWS, GCP, or Azure.
• Experience shipping a customer-facing Gen AI feature from proof-of-concept to production end-to-end.