We are seeking a Research Engineer who is passionate about building, deploying, and operating highly scalable, reliable, and performant AI solutions to delight millions of members. You will be instrumental in evolving our AI platform, methodologies, and infrastructure, contributing to both core research and its practical application.
We believe that strong AI systems are built upon solid scientific foundations, and we foster a culture of innovation, collaboration, and continuous learning. If you’re excited about making a significant impact on how millions discover and engage with content, we encourage you to apply.
About the Role:
Your responsibilities will include:
- Building, deploying, and operating highly scalable, reliable, and performant AI solutions.
- Evolving our AI platform, methodologies, and infrastructure.
- Contributing to both core research and its practical application.
- Collaborating cross-functionally with engineering, product, and research teams to deliver impactful AI features.
- Championing best practices for MLOps, CI/CD, testing, and monitoring.
- Driving innovation and continuous improvement in our AI systems.
About You:
We are looking for a highly skilled and motivated Research Engineer with a deep understanding of machine learning principles and practical experience in building and deploying AI systems at scale. The ideal candidate will possess a blend of research acumen, engineering excellence, and a passion for creating engaging member experiences.
Requirements:
- Minimum 7 years of industry experience in Machine Learning, AI, or related fields.
- Ph.D. or Master’s in Computer Science, Machine Learning, Statistics, or related technical fields, or equivalent practical experience.
- Solid background in Machine Learning, AI, Reinforcement Learning, or Causal Inference.
- Experience building and deploying large-scale ML systems in production environments.
- Proficiency in Python and Scala (or Java).
- Strong problem-solving, debugging, and analytical skills.
- Excellent communication and collaboration skills.
Nice to Have:
- Familiarity with distributed systems and cloud platforms (AWS, GCP, Azure).
- Experience with experimentation (A/B testing) and causal inference.
- Experience with various deep learning frameworks (TensorFlow, PyTorch) and Big Data technologies (Spark).
- Experience with model optimization, performance tuning, and explainable AI techniques.
- Familiarity with LLMs and their applications.
- Prior experience in recommender systems, ranking, or personalization is a plus.
