Summary of Responsibilities Job Summary The Staff Algorithm/AI Engineer is a senior technical expert responsible for designing, developing, and deploying advanced algorithms and artificial intelligence solutions to solve complex business problems. This role combines deep technical expertise in AI/ML with strong collaboration and leadership skills, influencing both project direction and organizational AI strategy. The Staff Engineer partners closely with cross-functional teams to deliver scalable and innovative AI-driven products, while mentoring junior engineers and acting as a subject matter expert. Responsibilities and Tasks
Design, develop, and implement scalable machine learning and AI algorithms for business-critical applications. Lead complex, cross-team AI/ML projects, driving technical direction, best practices, and innovation. Stay abreast of the latest advancements in AI/ML, and translate research into practical, deployable solutions. Work closely with product managers, data scientists, engineers, and business stakeholders to align AI solutions with organizational goals. Provide technical guidance, coaching, and mentorship to less experienced engineers and data scientists. Oversee the evaluation, validation, and monitoring of machine learning models, ensuring accuracy, fairness, and compliance. Set and enforce high standards for code quality, model documentation, and reproducibility. Contribute to the establishment and enforcement of AI/ML governance frameworks, ensuring responsible and ethical AI practices. Identify opportunities to optimize existing models and processes, driving efficiency and performance improvements.
Knowledge (Education/License/Certification, Prior Experience)
Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or related field; PhD preferred. 8+ years of experience in AI/ML engineering or related technical roles. Proven track record of delivering production-grade machine learning models and AI solutions.
Skills and Abilities
Technical Expertise: Recognized authority in AI/ML; drives innovation and sets technical direction. Collaboration & Influence: Builds strong cross-functional relationships; influences stakeholders and project outcomes. Leadership: Demonstrates thought leadership and mentors others; leads by example. Business Acumen: Understands business drivers; aligns technical solutions with strategic objectives. Adaptability: Embraces change, drives continuous learning, and adapts to evolving technologies. Communication: Articulates complex technical topics clearly; tailors communication to diverse audiences. Ethics & Integrity: Upholds high ethical standards; champions responsible AI practices.