Principal Applied Scientist, Generative AI

Location: Remote-USA; U.S. employees may live in any of the 50 United States, with limited exceptions.

Salary: $195,600–$312,400 annually in California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC; $185,800–$296,800 annually in Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia. The range depends on location and may not apply elsewhere.

Company

hirify.global is a U.S. real estate platform helping people navigate buying, selling, financing, and renting.

What you will do

• Define the research agenda for LLM post-training, reward modeling, and evaluation of agentic systems.
• Lead and grow applied scientists while providing technical direction, mentorship, and scientific rigor.
• Scope and solve ambiguous, high-impact problems from product vision through experiments, models, and data.
• Translate generative AI research into improvements for a product used by millions of home shoppers.
• Communicate scientific strategy and results to executives and cross-functional product, engineering, platform, and data partners.

Requirements

• PhD in Computer Science, Machine Learning, or a related field, or a master's degree with equivalent research experience.
• Deep, hands-on expertise in large language models or foundation models, including post-training such as SFT, DPO, RLHF, RFT/GRPO, reward modeling, or LLM evaluation.
• Experience leading others, either by managing teams of scientists or engineers while remaining technically hands-on, or by leading a research group with a strong publication record.
• Ability to independently scope and solve ambiguous problems and influence technical direction across teams.
• Proficiency in Python and machine learning frameworks such as PyTorch, including the ability to read, debug, and guide experimental code.

Nice to have

• Publications at top venues such as NeurIPS, ICML, ICLR, ACL, or EMNLP.
• Experience applying LLMs in consumer-facing products at scale.
• Experience with agentic AI systems and their evaluation.
• Background in reinforcement learning or preference learning.

Culture & Benefits

• Work remotely from a physical location of choice within the United States, subject to limited exceptions.
• Work within a flat team of 15–20 applied scientists where scientists own their areas and set direction.
• Collaborate with product, engineering, platform, and data teams.
• Receive competitive base salary and eligibility for equity awards based on experience, performance, and location.
• Participate in a distributed-work approach designed to provide flexibility and support innovation and inclusion.