Machine Learning Engineer / Data

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for seller, user, and transaction data.
• Build and optimize ETL processes to integrate and transform data for analytics platforms and business workflows.
• Analyze user behavior and develop meaningful business metrics and data-driven insights.
• Develop and enhance recommendation and personalization models to improve user experience and engagement.
• Build AI-powered search and ranking solutions to improve search relevance and overall platform performance.
• Develop AI solutions for OCR and face verification use cases.
• Process and manage real-time data streams and event-driven workflows using Apache Kafka.
• Work with MongoDB and Redis to support data management and improve application performance.
• Collaborate closely with Product and Engineering teams to develop and implement AI-powered features for the marketplace platform.

Qualifications

• 3+ years of experience in Machine Learning, Data Engineering, Data Analytics, or a related field.
• Strong programming skills in Python and/or Golang.
• Hands-on experience with ETL processes, data pipelines, and data modeling.
• Strong knowledge of SQL and experience working with databases such as MongoDB.
• Experience with Kafka for real-time data streaming and event-driven processing.
• Experience working with Redis or other caching technologies.
• Good understanding of Machine Learning, Recommendation Systems, Personalization, or NLP.
• Experience with AI Search, ranking, OCR, or face verification is a plus.
• Experience in E-commerce, Marketplace, Search Engine, or Personalization platforms is highly preferred.
• Experience with Microservices, REST API, gRPC, Docker, and Git is an advantage.

Technical Skills

Programming: Python, Golang
Data Engineering: ETL, Data Pipelines, Data Modeling, SQL
Machine Learning & AI: Recommendation Systems, Personalization, NLP, AI Search, Ranking, OCR, Face Verification
Database & Cache: MongoDB, Redis
Streaming: Apache Kafka, Real-time Data Processing
API & Communication: REST API, gRPC
Architecture: Microservices, Event-driven Architecture
DevOps & Tools: Docker, Git