Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global visual discovery platform is seeking an experienced engineering leader to join its Applied Science organization. The company helps millions of people discover creative ideas, explore possibilities, and plan meaningful experiences. Its Applied Science team develops advanced machine learning solutions that scale across engineering teams and support the platform’s core recommendation experiences.
The organization is committed to using artificial intelligence as a powerful partner that enhances creativity, improves productivity, and expands the impact of its products. The Applied Science team plays a critical role in developing cutting-edge machine learning technologies and bringing research breakthroughs into production at significant scale.
What You Will Do
Vision and Strategy
- Own the technical roadmap and strategic vision for next-generation recommendation systems.
- Champion state-of-the-art machine learning techniques to drive innovation in recommendation technology.
- Define strategic priorities that balance near-term business requirements with long-term research opportunities.
Research to Production
- Transition breakthrough machine learning research into production-ready systems.
- Develop solutions that directly contribute to important company and product metrics.
- Establish effective processes for moving innovative research concepts from experimentation to scalable production environments.
Team Leadership and Culture
- Manage, inspire, and develop a talented team of machine learning researchers and engineers specializing in recommendation systems.
- Partner with team members to define their charter and technical direction.
- Maintain a strong balance between cutting-edge research and foundational machine learning capabilities.
- Develop reusable embeddings and other foundational technologies that can benefit products across the organization.
- Mentor and coach engineers and researchers to support their professional growth.
Cross-Functional Collaboration
- Collaborate with Core Engineering, Ads Engineering, Infrastructure, Content, and Data Science teams to prototype, build, and scale complex solutions.
- Partner with senior leadership to deepen understanding of user needs and behavior.
- Help establish the strategic direction for recommendation system development.
- Influence technical and product decisions through data-driven insights and strong technical expertise.
What We Are Looking For
- 7+ years of combined post-graduate academic and industry experience applying state-of-the-art machine learning technologies to real-world problems involving web-scale data.
- 3+ years of direct people management experience.
- Proven track record of delivering high-impact initiatives across multiple product areas.
- Demonstrated ability to influence peers, technical teams, and senior leadership using data-driven insights.
- Experience mentoring, coaching, and developing software and machine learning engineers.
- Strong ability to stay current with industry trends, emerging technologies, tools, and methodologies.
- Experience developing proof-of-concept prototypes and evaluating emerging machine learning approaches.
- Strong business and product judgment, including the ability to transform ambiguous questions into clearly defined projects with measurable success criteria.
- Excellent communication skills with the ability to explain complex technical findings to leadership and product teams.
- Strong technical credibility supported by publications or research contributions in machine learning, artificial intelligence, data science, or related fields.
- Master’s or PhD degree in Computer Science, Machine Learning, Natural Language Processing, Statistics, Information Sciences, or a related technical field.
Nice to Have
- Track record of publishing research at leading machine learning and recommendation systems conferences such as KDD, RecSys, NeurIPS, or CVPR.
- Experience leveraging modern Large Language Model and agentic workflows.
- Experience applying Generative AI capabilities to improve engineering productivity and accelerate context extraction.
- Strong understanding of modern recommendation system architectures and techniques.
- Experience working with large-scale machine learning systems and production environments.
Disclaimer
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- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
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