Software Engineer - Machine Learning, Trust and Safety at Mercari, Inc. (India)

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

24 Mar, 26

Salary

0.0

Posted On

24 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Recommendation Systems, Data Analysis, Cloud Computing, Kubernetes, TensorFlow, PyTorch, MLOps, Backend Engineering, Docker, AI, Anomaly Detection, Content Moderation, Microservices, Deep Learning, Statistical Analysis

Industry

technology;Information and Internet

Description

About Us Mercari is a Japan-based C2C marketplace company founded in 2013 with the mission to “Create value in a global marketplace where anyone can buy & sell.” From being the first tech unicorn from Japan before its IPO in 2018 we have come a long way towards becoming a global player and continuously and diligently work towards our transformation journey with a strong focus on our mission. Since its inception, Mercari Group has worked to grow its services, investing in both our people and technology. Over time Mercari has expanded from being the top player in the C2C marketplace in Japan to new geographies like the U.S. We have also successfully launched new businesses such as Merpay, which is a mobile payment service platform with a vision to create a society where anyone can realize their dreams through a new ecosystem centered not only on payment service but also on credit. Today, Mercari Group is made up of multiple subsidiary businesses including logistics, B2C platform, blockchain, and sports team management. For our services to be utilized by people worldwide; however, there is still a mountain of work ahead of us. This endeavor naturally requires the capability of the best talent and minds, and that is exactly the reason for us to launch the India Center of Excellence. With your help, we will continue to take on the world stage and strive to grow into a successful global tech company. Our Culture To achieve our mission at Mercari, our organization and each of our employees share the same values and perspectives. Our individual guidelines for action are defined by our four values: Go Bold, All for One, Be a Pro and Move Fast. Our organization is also shaped by our four foundations: Sustainability, Diversity & Inclusion, Trust & Openness, and Well-being for Performance. Regardless of how big Mercari gets, the culture will remain essential to achieving our mission and something we want to preserve throughout our organization. We invite you to read the Mercari Culture Doc which summarizes the behaviors and mindset shared by Mercari and its employees. We continue to build an environment where all of our members of diverse backgrounds are accepted and recognized, and where they can thrive while holding dear to Mercari’s culture. Work 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 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. Minimum Requirements Over 2-6 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 AI-based anomaly detection and content moderation systems is preferred 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 Employment Status Full-time Office Bangalore Hybrid workstyle We believe in high performance and professionalism. We work from office for 2 days/week and work from home 3 days/week To build a strong & highly-engaged organization in India, we highly encourage everyone to work from our Bangalore office, especially during the initial office setup phase We will continue to review and update the policy to address future organizational needs Work Hours Full flextime (no core time) *Flexible to choose working hours other than team common meetings Media Owned Media Mercari Engineering Portal AI at Mercari portal Mercan - Introduces the people that make Mercari Mercari US Blog Related Articles Personalize to globalize:How Mercari is reshaping their app, their company, and the world | mercan The Providers of the Safe and Secure Mercari Experience: The TnS Team, Introduced by Its Members! | mercan

Responsibilities

Develop and optimize machine learning algorithms and models to enhance the recommendation system, improving the user discovery experience. Collaborate with cross-functional teams to gather requirements and implement features that enhance user engagement.