Senior Applied Scientist (Post-Training)
Zillow Open At a glance
Senior AI Research role at Zillow. Remote, United States · full-time.
In listing AI Research salary
remoteroles summary, based on the employer's posting.
What you'll do
- Run LLM post-training from start to finish, including supervised fine-tuning, preference optimization and reinforcement-based methods on GPUs
- Train reward models across categories to turn paired preferences into scalar scores
- Assess live agent paths with judge-style LLMs and create reward functions that generalize from offline rubrics to production traces
- Lead unclear, complex projects through delivery with partner teams, and mentor scientists while moving AI research into production
What you bring
- A master's degree or above in computer science or a related discipline
- Practical experience with LLM post-training and reinforcement fine-tuning, including complete GPU training runs
- Research experience developing reward models, plus strong grounding in generative AI, transformers, reinforcement learning and preference learning
- Strong Python skills and experience using PyTorch, TensorFlow or another listed framework
Who this fits
This remote role is for a senior scientist who can independently shape ambiguous work and provide technical guidance to scientists and machine-learning engineers. You may work from a physical location you choose within the United States, subject to limited state exceptions, and must identify that location to the company.
From the employer
About the team
The Agentic Foundations team is a focused group of 15–20 applied scientists within Zillow's broader Agentic AI organization, building the foundational AI technologies that power the next generation of home shopping experiences. This Senior Applied Scientist will focus on model post-training and reward modeling — the science that lets our agents measurably improve over time as part of a self-evolving agentic system. The role will drive complex, ambiguous work end-to-end, partnering closely with product, engineering, science, platform, and data teams to translate the latest advances in LLMs, reinforcement learning, and post-training into production impact. This is an exciting time to join as Zillow is building agentic skills across the full home-shopping journey — from search and personalized guidance to offer strategy and financing — at a scale of hundreds of millions of requests per day.About the role
Role and responsibilities:
Own LLM post-training pipelines — SFT, DPO, and reinforcement fine-tuning (RFT/GRPO) — running training end-to-end on GPU infrastructure.
Build and train fast, multi-category reward models (PRMs) that emit scalar signals from contrastive preference pairs.
Design on-policy and online assessment: score live agent trajectories using LLM-as-a-Judge frameworks.
Translate offline evaluation rubrics into generalizable reward functions that work on arbitrary production traces.
Independently drive complex work end-to-end by collaborating across partner teams.
Provide technical leadership and mentorship while helping translate state-of-the-art AI research into production impact.
Who you are
Master's degree or higher in Computer Science or a related field.
Hands-on experience with LLM post-training and RL fine-tuning: SFT, DPO, RFT/GRPO, running end-to-end training runs on GPU infrastructure.
Exposure to reward model development — research-level experience is sufficient; production deployment is not required.
Strong knowledge of generative AI, including foundation models, transformers, reinforcement learning, and preference learning.
Ability to independently scope and solve ambiguous problems end-to-end while providing technical leadership to scientists and MLEs.
Strong programming skills, especially Python, plus experience with ML frameworks such as PyTorch or TensorFlow.
Nice-to-haves:
PhD in Computer Science, Machine Learning, or a related field.
Experience evaluating agentic AI: multi-turn trace analysis, LLM-as-a-Judge, and the interaction between offline evals and online monitoring.
Published work in post-training, RLHF/RLAIF, preference learning, or reward modeling.
Experience with GPU training platforms such as Databricks or Fireworks.
Get to know us
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 people navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company reshaping an industry and helping more people make home a reality.
How we work is a key part of that transformation. Through Cloud HQ, our strategic approach to distributed work, most employees have the flexibility to work from wherever they’re most productive—enabling us to move fast, stay connected and deliver on our people promise.
Zillow is honored to be recognized among the best workplaces in the U.S. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2026, and included on TIME’s America’s Best Companies 2026 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.
No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.
Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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