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
• 2+ years of programming experience in a relevant programming language
• 1+ years of hands-on experience in one or more of the following areas: machine learning, recommendation systems, llms or artificial intelligence
• Experience with scripting languages such as Python, Javascript or Hack
• Experience with developing machine learning models at scale from inception to business impact
• Knowledge developing and debugging in C/C++ and Java, or experience with scripting languages such as Python, Perl, PHP, and/or shell scripts
• Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships
• Proven experience designing, building, or deploying recommendation systems (e.g., collaborative filtering, content-based, hybrid approaches, personalization at scale)
• 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

Preferred Qualifications
• Masters degree or PhD in Computer Science or another ML-related field
• Exposure to architectural patterns of large scale software applications
• Experience with scripting languages such as Pytorch and TensorFlow
• Publications in top-tier conferences/journals, patents, or open-source contributions in the recommendations or LLM space
• Hands-on experience working with large language models (LLMs), such as BERT, GPT, or similar architectures, including fine-tuning, integration, or application in production environments
• 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