About Us:
Across the globe, rapid urbanization and escalating climate change impacts are driving skyrocketing risks from disasters like earthquakes, hurricanes, and wildfires—yet exposed building inventories are unstandardized, static, and incomplete, preventing decision making across verticals, from public policy to real estate transactions. Decision today is made with incomplete and even wrong property information.
At ResiQuant, we're on a mission to empower insurers, financial institutions, and asset managers with AI systems trained on structural engineering domain knowledge that can fill in the gaps and provide engineering-relevant building characteristics.
Founded by Stanford PhDs and backed by Pear VC, ResiQuant is driven by an unwavering commitment to protect communities and businesses from the devastating impacts of disasters. We believe that every organization deserves access to best-in-class property risk intelligence to build resilience against the storms to come—and we won't stop until this is the norm, not the exception.
About You:
We're seeking an individual who is passionate about the mission of the company to join us as an AI Research Engineer with a focus on computer vision and vision-language model fine tuning. We prize candidates that are motivated by a mission driven enterprise and are ready to help foster an inclusive and collaborative culture. As a lean seed startup, we need someone with a scrappy, hands-on approach, eager to evolve alongside our team, and support the company in all stages of growth. The ideal candidate is excited to apply their knowledge in machine learning, LLMs, and computer vision, to shape the trajectory of a groundbreaking company.
Start date: Immediate
Qualifications:
Background in Computer Science and full stack development. Some research experience in AI/ML preferred.
Experience with Computer Vision models in the academic and/or practical environment.
Experience building RAGs and fine-tuning LLMs.
What will make you stand out:
Ph.D. in CS with focus on computer vision and/or LLMs.
Experience with AI applications using satellite and geospatial imagery.
Conference and/or journal publications on ML, deep learning, or LLMs.
Experience working with multimodal data sources (e.g., voice, imagery, text) for AI model training and fine-tuning.
Proficiency/Experience collecting and interpreting data from interviews.
What drives us:
Impact: we are driven by a shared mission to address a paramount challenge of our time
Resolve: we believe that hard work and resilience yield extraordinary outcomes
Urgency: we are motivated to outpace rapid urbanization and escalating disaster impacts
Why join RQ:
Opportunity to be involved in an early-stage startup and build the culture you want to see.
Chance to pioneer and disrupt one of the world's largest industries.
Experience firsthand the tangible impact of what you build.
Day to day:
Research and deploy architectures for AI systems trained on structural engineering and disaster risk domain expertise for classification tasks.
Participate in product ideation and development.
Interface with product managers, software development, and AI team to understand product goals and data needs.
Write, test, document, and review code according to RQ’s development standards that you would help to define.
What we offer:
Competitive salary commensurate with experience
Equity in the company as an early stage member
Vibrant tech startup environment
Competitive company 401(k) program with company matching
Health insurance
Working on the challenge of our generation with other passionate people
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