Software Engineer

Job Title: Software Engineer (Machine Learning & Recommendation)

About the Role:

Mercari is seeking experienced Machine Learning Engineers to join our Recommendation domain team in Bengaluru, India. In this role, you will be instrumental in developing and maintaining machine learning systems, including sophisticated recommender systems, to enhance the functionality and services of the Mercari marketplace app. You will leverage cutting-edge infrastructure and company-wide platform tools to deliver a more convenient, safer, and enjoyable marketplace experience for our users worldwide. We are committed to applying advanced machine learning technologies and utilize cloud environments with Kubernetes for operating and improving our ML systems.

What You'll Do:

• Develop and optimize machine learning algorithms and models to significantly improve our recommendation system and enhance user discovery experiences.
• Collaborate closely with cross-functional teams and product stakeholders to define requirements, design innovative solutions, and implement features that boost user engagement.
• Conduct in-depth data analysis and large-scale experimentation to uncover patterns, trends, and insights crucial for refining recommendation algorithms.
• Utilize leading machine learning frameworks and libraries to deploy scalable and efficient recommendation solutions.
• Monitor system performance rigorously and conduct A/B testing to measure the effectiveness of implemented features.
• Proactively research and stay abreast of the latest advancements in AI/machine learning, recommending and implementing innovative approaches to elevate our recommendation capabilities.

Who You Are:

Minimum Qualifications:

• Possess 2-4 years of professional experience in the end-to-end development of large-scale Machine Learning systems in production environments.
• Demonstrate strong experience in developing and delivering complete machine learning solutions, from initial experimentation to model deployment, including backend engineering and MLOps best practices in production systems.
• Proficient with common machine learning frameworks such as TensorFlow or PyTorch, and libraries like scikit-learn, NumPy, and pandas.
• Exhibit a deep understanding of core machine learning concepts and software engineering fundamentals.
• Have basic knowledge and practical skills in system monitoring, logging, and common production environment operations.
• Possess effective communication skills to facilitate successful project collaboration across multiple teams and stakeholders.

Preferred Qualifications:

• Previous experience developing Recommender systems using large-scale datasets.
• Familiarity with enterprise search systems and related technologies (e.g., ELK stack).
• Proficiency in functional development and bug fixing to enhance system performance and reliability.
• Experience with containerization and orchestration technologies like Docker and Kubernetes.
• Hands-on experience with major cloud platforms (AWS, GCP, Microsoft Azure, etc.).
• Experience with microservice development and operation using Docker and Kubernetes.
• Experience utilizing deep learning models or Large Language Models (LLMs) in production.
• A track record of publications in top-tier peer-reviewed conferences or journals is a plus.

About Mercari India Center of Excellence:

The India Center of Excellence is a vital part of Mercari's global expansion, dedicated to driving innovation and technological excellence. We are building an environment where engineers can pursue bold challenges, utilize cutting-edge technologies, make autonomous decisions, and operate at a rapid pace. Join us in shaping the future of global e-commerce.

Work Style:

• Employment Type: Full-time, Permanent
• Location: Bengaluru, India
• Hybrid Work: We embrace a hybrid work model, requiring 2 days in the office per week and offering 3 days of remote work.
• Office Engagement: To foster a strong and engaged organization in India during our initial setup phase, we highly encourage working from our Bangalore office.
• Work Hours: Full flextime with no core hours, offering flexibility to choose working hours outside of team common meetings.