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Zillow

Principal Applied Scientist, Agentic AI

RemoteUnited States only
Published
Role
AI / ML
Experience
Principal
Employment
Full-time
Company size
Enterprise
$191.3k–$305.7k/yr
Check eligibility

Open to US only. Set where you work from to check your eligibility.

No BS summary

Principal Applied Scientist with PhD or equivalent experience in AI/ML, focusing on RL post-training for large models. Must have strong expertise in post-training techniques (SFT, DPO, RLHF/RLAIF, preference modeling), evaluation/monitoring of aligned models, and modern transformer-based models (LLMs). Experience with cross-functional partners in high-stakes domains is required. Technical leadership and mentorship are key.

Core skills

reinforcement learningRL post-traininglarge models

Required skills

post-trainingsupervised fine-tuningDPORLHFRLAIFpreference modelingmulti-objective optimizationevaluationmonitoring of aligned modelswin-rate experimentshuman feedback loopsAI feedback loopslong-horizon evaluationsafety metricsguardrail metricstransformer-based modelsLLMsmultimodal modelsvector searchorchestration frameworks

Required languages

English

What you'll do

  • Lead the technical direction and strategy for RL post-training of production models, partnering with other scientists, engineers, and product leaders to align models with customer and business needs.
  • Design and implement post-training pipelines that combine techniques such as supervised fine-tuning on curated demonstrations, preference modeling and pairwise ranking, and RL-based alignment approaches like RLHF, RLAIF, or DPO for multi-objective optimization.
  • Develop reward models and objective formulations that balance constraints such as helpfulness, safety, fairness, compliance, and customer satisfaction, and iterate on them using human and AI feedback at scale through online and batch adaptation loops with strong guardrails.
  • Translate conversational logs, behavioral signals, and structured attributes into training, reward, and evaluation signals for post-training and reinforcement learning, turning heterogeneous data into actionable supervision.
  • Partner with model and platform teams to improve the efficiency and robustness of training and evaluation, including off-policy evaluation, replay strategies, controlled rollouts, and metrics and evaluation frameworks such as win-rates versus baselines, safety and quality metrics, and expert-review programs.
  • Mentor applied scientists and engineers, raising the technical bar in RL, post-training, and evaluation, and contributing to the broader AI roadmap at Zillow through thought leadership and guidance.
  • When appropriate, represent Zillow’s work externally through talks, publications, or open-source contributions.

What they require

  • You are an applied scientist who is excited to use reinforcement learning and post-training methods to shape how AI systems behave in complex, high-judgment settings, and you are comfortable owning ambiguous problems end‑to‑end—from framing the objective and data strategy to shipping models into production and measuring their impact.
  • You have a PhD or equivalent experience in Computer Science, Electrical Engineering, Statistics, or a related field, with emphasis in areas such as reinforcement learning, bandits, large language models, or applied machine learning.
  • You have strong, current expertise in post-training techniques (such as supervised fine‑tuning, DPO, RLHF/RLAIF, preference modeling, and multi‑objective optimization), in evaluation and monitoring of aligned models (including win‑rate experiments, human and AI feedback loops, long‑horizon evaluation, and safety or guardrail metrics), and in modern transformer‑based models and tooling such as LLMs, multimodal models, vector search, and orchestration frameworks.
  • You have experience working with cross‑functional partners (for example, engineering, product, design, operations, legal, and compliance) in domains where safety, trust, or regulation matter, such as marketplaces, finance, healthcare, or other high‑stakes verticals.
  • You demonstrate technical leadership and mentorship, helping senior engineers and scientists grow, creating clarity amid ambiguity, and driving alignment across teams, and you communicate complex technical ideas clearly to both expert and non‑expert audiences in writing and verbally.
  • Here at Zillow, we value the experience and perspective of candidates with non‑traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences.

Benefits

  • In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location.
  • Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence.

Real EstateEnterprisezillow.com/

What people say about this company

3.8/ 5

$191.3k–$305.7k/yr