Hao Fu
AI EngineerSoftware Engineer at Uber
Uber
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineer at Uber
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
In the past 5 years, I co-built a growth experiment (A/B test) platform and a marketing personalizer to incorporate data-driven strategies into Uber's growth & marketing. I am passionate about building AI powered applications using big data, backend, ML and LLM technologies.
University of California, Berkeley
Bachelor of Arts (B.A.), Computer Science
September 1, 2015 – Present
Uber
Software Engineer
August 1, 2019 – Present
Greater Seattle Area
Amazon
Software Engineer
October 1, 2015 – July 1, 2019
Greater Seattle Area
Cultural Fit Analysis
The candidate has a strong background in large, product-driven tech companies (Amazon, Uber) with a clear focus on applying machine learning to user-facing products. This aligns well with a culture that values data-driven decision-making and scalable ML solutions. The experience in building growth platforms and personalization systems demonstrates an understanding of business impact and user engagement, which is crucial for an AI Engineer role. However, the resume does not provide information on project diversity outside of personalization/recommendation systems, which limits the assessment of broader cultural fit or adaptability to different problem domains.
Soft Skills & Operational Fit
The candidate's experience descriptions suggest strong problem-solving skills and a proactive approach to system design and evolution. The focus on 'pioneering' and 'revolutionizing' indicates leadership potential and a drive for innovation. However, without psychometric test results or interview data, a definitive assessment of soft skills like teamwork, stress handling, or communication clarity in a collaborative setting cannot be made.