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.
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