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 and inspiration platform connects hundreds of millions of people with ideas and possibilities across areas such as shopping, lifestyle, creativity, and personal interests. Its engineering organization develops highly scalable technologies that help personalize experiences and enable users to discover relevant content.
The company is investing heavily in artificial intelligence and machine learning to enhance personalization and product experiences. Engineering teams work with large-scale datasets and advanced recommendation technologies to develop systems that serve hundreds of millions of users globally.
The organization is seeking a Machine Learning Engineer, Core Engineering to develop advanced machine learning and deep learning technologies that power personalized experiences. The role will involve designing and improving large-scale recommendation systems while collaborating with teams across multiple product areas.
The successful candidate will work with large datasets, experiment with machine learning models, and contribute to high-impact systems across areas such as Homefeed, Ads, Growth, Shopping, and Search.
Key Responsibilities
- Build cutting-edge technologies using the latest advances in deep learning and machine learning to personalize user experiences.
- Partner with cross-functional engineering and product teams to experiment with and improve machine learning models across different product surfaces.
- Develop data-driven approaches that leverage unique data characteristics to improve candidate retrieval and recommendation quality.
- Design and implement scalable machine learning systems and data processing pipelines.
- Work in a high-impact engineering environment focused on rapid experimentation and product launches.
- Research and apply emerging industry trends in recommendation systems and machine learning.
- Collaborate with other engineers and teams to understand how machine learning can be applied across different product areas.
- Contribute to the development of scalable systems capable of processing large volumes of data.
- Apply machine learning techniques to solve complex personalization, ranking, search, and recommendation challenges.
Required Qualifications
- 2+ years of industry experience applying machine learning methods such as user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, or graph representation learning.
- Hands-on experience building data processing pipelines and large-scale machine learning systems.
- Experience working with big data technologies such as Hadoop and Spark.
- Bachelor’s degree in computer science, machine learning, statistics, a related technical field, or equivalent professional experience.
- Strong understanding of machine learning principles and their practical application.
- Experience working with data-driven experimentation and model development.
- Ability to collaborate effectively with engineering and cross-functional teams.
Preferred Qualifications
- Master’s degree or PhD in Machine Learning or a related technical field.
- Publications at leading machine learning conferences.
- Experience using AI coding assistants such as Cursor, Copilot, Codex, or similar tools for development, debugging, testing, and refactoring.
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL and data exploration, and engineering workflow acceleration.
- Expertise in scalable real-time systems that process streaming data.
- Experience with large-scale recommendation systems.
- Strong interest in applied machine learning and consumer technology products.
- Passion for developing innovative machine learning solutions that improve user experiences.
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