Responsibilities
- 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 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.
- Develop and optimize machine learning algorithms and models to enhance the 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 machine learning techniques and recommend innovative approaches to enhance recommendation capabilities.
Requirements
- 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.
- Strong analytical and problem-solving skills
- Basic knowledge and skills related to monitoring system, logging, and common operations
- Communication skills to carry out projects in collaboration with multiple teams and stakeholders
- Possess strong product engineering mindset
Nice to haves
While not specifically required, tell us if you have any of the following.
- Experience developing Recommender systems utilizing large-scale data sets
- Functional development and bug fixing skills necessary to improve system performance and reliability
- Using container technology such as Docker and Kubernetes
- Using cloud platforms (AWS, GCP, Microsoft Azure, etc.)
- Microservice development and operation experience with Docker and Kubernetes
- Utilizing deep learning models in production
- Japanese language ability
