AI Developer for Recommendation Systems

20 hours ago


Aurangabad, Maharashtra, India beBeeAI Full time ₹ 1,00,00,000 - ₹ 2,00,00,000
Job Title: AI Developer for Recommendation Systems

About Us

We are a cutting-edge tech company with a mission to create value in a global marketplace where anyone can buy & sell.

Our organization has expanded rapidly since its inception, from being the first tech unicorn in Japan before our IPO in 2018, we have expanded into new geographies like the U.S. and launched new businesses such as Merpay.

Today, we consist of multiple subsidiary businesses including logistics, B2C platform, blockchain, and sports team management.

Our mission at our company requires the capability of the best talent and minds. That's why we're launching the India Center of Excellence.

Culture Overview

We share the same values and perspectives in our organization and employees. Our individual guidelines for action are defined by our four core values: Be Proactive, Collaborative, Innovative, and Adaptable.

Our organization is also shaped by our four pillars: Sustainability, Diversity & Inclusion, Trust & Openness, and Well-being for Performance.

We build an environment where all members of diverse backgrounds are accepted and recognized, and where they can thrive while holding dear to our culture.

Job Responsibilities

  • Develop sophisticated AI systems like Recommender systems to enhance the functions and services of our marketplace app.
  • Utilize cloud and Kubernetes to operate and improve AI systems.

Bold Challenges

  • Develop and optimize AI algorithms and models to elevate recommendation system performance.
  • Collaborate with cross-functional teams and product stakeholders to gather requirements, design solutions, and implement features that boost user engagement.
  • Conduct data analysis and experimentation with large-scale data sets to identify patterns, trends, and insights that drive the refinement of recommendation algorithms.
  • Employ AI frameworks and libraries to deploy scalable and efficient recommendation solutions.
  • Monitor system performance and conduct A/B testing to evaluate the effectiveness of features.
  • Continuously research and stay updated on advancements in AI techniques and recommend innovative approaches to enhance recommendation capabilities.


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