Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
• Implement custom user interfaces using latest programming techniques and technologies
• Develop reusable software components for interfacing with back-end platforms
• Analyze and optimize code for quality, efficiency, and performance
• Lead complex technical or product efforts and provide technical guidance to peers
• Architect efficient and scalable systems that drive complex applications
• Identify and resolve performance and scalability issues
• Work on a variety of coding languages and technologies
• Establish ownership of components, features, or systems with expert end-to-end understanding
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships
• 6+ years of programming experience in a relevant language or 3+ years of experience + PhD
• Experience building maintainable and testable code bases, including API design and unit testing techniques
Preferred Qualifications
• Experience building and shipping high quality work and achieving high reliability
• Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes
• Experience with developing machine learning models at scale from inception to business impact
• Exposure to architectural patterns of large scale software applications
• Experience with scripting languages such as PyTorch, TensorFlow, Python, JavaScript or Hack
• 2+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or a related technical field
• Knowledge developing and debugging in C/C++ and Java
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
