Senior Machine Learning Engineer - Recommendation Systems

Title: Senior Machine Learning Engineer - Recommendation Systems

Company:

Rebuy is a SaaS application that is redefining data-powered shopping experiences with a new breed of personalization and merchandising solutions, which turn intelligence into revenue-generating actions.

We offer onsite solutions, marketing tools and automation, RESTful API, JavaScript Library, and more to help supercharge high-growth brands.

Rebuy is a fully remote company and trusted by some of the fastest-growing brands in DTC such as Magic Spoon, Olipop, Liquid Death, Blendjet and many more.

We value empathy, hard work and respect. Each team member plays a significant role in the company, and is helping to shape the future of intelligent commerce. We build strong and lasting partnerships with all of our merchants and partners, provide a safe and fun work environment, and truly love what we do.

About the role:

We are seeking a Senior Machine Learning Engineer with a passion for recommendation systems to join our team. As a member of the ML/AI team, you will be instrumental in developing and enhancing our personalized recommendation capabilities using cutting-edge machine and deep learning techniques. You'll play a key role in shaping the technical direction of our recommendation systems, driving innovation and improving user experiences.

The ideal candidate will have a deep understanding of recommendation system algorithms, experience building and scaling machine learning models, and a collaborative spirit. If you're excited about the potential of AI to deliver personalized recommendations and want to make a significant impact on our users, we encourage you to apply.

What you’ll do:

• Design and Implement: Develop state-of-the-art recommendation algorithms and models, including collaborative filtering, content-based filtering, and hybrid approaches.
• Optimize and Scale: Continuously improve recommendation performance through experimentation, feature engineering, and model tuning. Scale models to handle large datasets and real-time recommendations.
• Personalize: Build personalized user profiles and tailor recommendations based on individual preferences, behaviors, and context.
• Evaluate and Measure: Establish metrics to assess the effectiveness of recommendations and drive data-driven improvements.
• Collaborate: Work closely with cross-functional teams, including product managers, data engineers, and backend engineers, to integrate and deploy recommendation systems.

Requirements:

• Recommendation Expertise: Strong experience with recommendation system algorithms, architectures, and evaluation metrics.
• Machine Learning Mastery: Proficiency in Python, PyTorch, and other relevant ML frameworks. Experience training and deploying machine learning models at scale.
• Data Skills: Ability to work with large datasets, perform feature engineering, and build data pipelines.
• Collaborative: Excellent communication and collaboration skills to work effectively with a multidisciplinary team.

The ideal candidate:

• Recommendation Enthusiast: Keeps up-to-date with the latest research and trends in recommendation systems.
• Problem Solver: Proactively identifies and addresses challenges in recommendation model performance.
• Passionate: Enthusiastic about leveraging AI to create personalized user experiences.
• M.Sc. Degree or equivalent work experience.
• 5+ years of experience in building and deploying production-level machine learning systems, with a focus on recommendation systems.

Nice to have:

• Experience with:
  • Large language models (LLMs) for recommendation tasks.
  • Reinforcement learning for optimizing recommendation policies.
  • Graph-based recommendation algorithms.
• Familiarity with:
  • Natural language processing (NLP) techniques for analyzing user feedback and preferences.
  • A/B testing frameworks for evaluating recommendation algorithms.

Benefits

Rebuy is a fully remote company and we provide our employees with everything they need to succeed both professionally and personally.

• Work from anywhere (with a strong internet connection)
• 100% free health, dental, and vision insurance for you and your family
• Flexible vacation, paid holidays, parental leave, and sick leave policies
• 401(k) retirement plan
• Company contributes 3% of your salary as a 401(k) bonus (no vesting)
• Amazing team of highly talented and driven people, redefining intelligent commerce