Sr. Machine Learning Engineer, Core Engineering

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 connects hundreds of millions of users with creative ideas and inspiration. Its engineering organization develops large-scale machine learning systems that power personalized experiences across multiple product areas, including recommendations, search, advertising, shopping, and growth.

The organization places a strong emphasis on artificial intelligence as a tool that augments creativity and engineering impact. Teams work with extensive datasets and large-scale recommendation systems while maintaining a collaborative environment focused on experimentation, innovation, and continuous learning.

The organization is seeking a Sr. Machine Learning Engineer, Core Engineering to develop advanced machine learning technology that powers personalized experiences. This role will work closely with teams across the organization to experiment with and improve machine learning models across multiple product surfaces.

The role provides an opportunity to work with large-scale data, recommendation systems, and modern machine learning technologies while contributing to products used by hundreds of millions of people worldwide.

Key Responsibilities

• Build cutting-edge technology using the latest advances in deep learning and machine learning to deliver personalized user experiences.
• Partner closely with teams across the organization to experiment with and improve machine learning models for Homefeed, Ads, Growth, Shopping, and Search.
• Develop data-driven methods that leverage unique data properties to improve candidate retrieval and recommendation quality.
• Build and improve large-scale machine learning systems and data processing pipelines.
• Work in a high-impact environment focused on rapid experimentation and product launches.
• Apply machine learning techniques to solve complex problems involving personalization, recommendation, search, ranking, and related areas.
• Keep up with industry trends and advances in recommendation systems and machine learning.
• Collaborate across engineering and product teams to translate machine learning capabilities into impactful user experiences.
• Contribute to scalable systems capable of processing large volumes of data efficiently.

Required Qualifications

• 4+ years of industry experience applying machine learning methods.
• Experience with areas such as user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, or graph representation learning.
• End-to-end hands-on experience building data processing pipelines and large-scale machine learning systems.
• Experience with big data technologies such as Hadoop and Spark.
• Bachelor’s degree in computer science, machine learning, statistics, or a related field, or equivalent experience.
• Strong understanding of machine learning concepts and their practical application in production environments.
• Ability to work collaboratively with cross-functional engineering and product teams.

Preferred Qualifications

• 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.
• Passion for applied machine learning and consumer-facing products.
• Master’s or PhD in Computer Science, Machine Learning, NLP, Statistics, Information Sciences, or a related field, or equivalent professional experience.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.