Machine learning engineers working in the Recommendation domain develop the functions and services of the marketplace app Mercari through the development and maintenance of machine learning systems like Recommender systems while leveraging necessary infrastructure and companywide platform tools.
Mercari is actively applying advanced machine learning technology to provide a more convenient, safer, and more enjoyable marketplace. Machine learning engineers use the cloud and Kubernetes to operate and improve machine learning systems.

Bold Challenges

We are looking for people who are interested in our services, mission, and values, and want to work where engineers can go bold, use the latest technology, make autonomous decisions, and take on challenges at a rapid pace.
Develop and optimize machine learning algorithms and models to enhance recommendation system to improve discovery experience of users
Collaborate with cross-functional teams and product stakeholders to gather requirements, design solutions, and implement features that improve 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
Utilize machine learning 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/machine learning techniques and recommend innovative approaches to enhance recommendation capabilities.

Over 5-9 years of professional experience in end-to-end development of large-scale ML systems in production
Strong experience demonstrating development and delivery of end-to-end machine learning solutions starting from experimentation to deploying models, including backend engineering and MLOps, in large scale production systems.
Experience using common machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, NumPy, pandas)
Deep understanding of machine learning and software engineering fundamentals
Basic knowledge and skills related to monitoring system, logging, and common operations in production environment
Communication skills to carry out projects in collaboration with multiple teams and stakeholders

Preferred skills

Experience developing Recommender systems utilizing large-scale data sets
Basic knowledge of enterprise search systems and related stacks (e.g. ELK)
Functional development and bug fixing skills necessary to improve system performance and reliability
Experience with technology such as Docker and Kubernetes
Experience with cloud platforms (AWS, GCP, Microsoft Azure, etc.)
Microservice development and operation experience with Docker and Kubernetes
Utilizing deep learning models/LLMs in production
Experience in publications at top-tier peer-reviewed conferences or journals

Software Engineer – Machine Learning, Recommendation

Key skills