全职 Machine Learning Engineer 工作, 薪水, CLPS Global 公司招聘中 - Ricebowl

About the Company

CLPS RiDiKRiDiK is a global technology solutions provider and a subsidiary of CLPS Incorporation (NASDAQ: CLPS), delivering cutting-edge end-to-end services across banking, wealth management, and e-commerce. With deep expertise in AI, cloud, big data, and blockchain, we support clients across Asia, North America, and the Middle East in driving digital transformation and achieving sustainable growth. Operating from regional hubs in 10 countries and backed by a global delivery network, we combine local insight with technical excellence to deliver real, measurable impact. Join RiDiK and be part of an innovative, fast-growing team shaping the future of technology across industries.

About the Role

We are hiring Machine Learning Engineer banking domain.

Responsibilities

Key Responsibilities:

Design and deliver scalable real-time data and machine learning solutions by building robust ingestion and transformation frameworks across Hadoop ecosystems. Enable end-to-end ML model operationalization and performance optimization, while supporting multi-modal data processing and development of engineering tools and applications

• Design and develop highly scalable, Real time systems using Hadoop ecosystem components(Iceberg, Spark, Ozone, Trino, Hive, Ranger, Kafka, Flink and Nifi)
• Build robust data ingestion and transformation frameworks using Java, Spark, Python, and shell scripting for ingesting multi model data(image, audio, video, unstructured documents) with both batch and real-time.
• Develop full‑stack applications and internal engineering tools using Python, shell scripting, and modern web frameworks (e.g., Flask, React).
• Collaborate closely with data scientists to operationalize machine learning models using Cloudera Machine Learning (CML).
• Perform performance tuning and optimization of data applications on Hadoop to ensure optimal resource utilization.
• Experience working with ML platforms such as CML, Spark MLlib, and Python ML libraries (scikit‑learn, XGBoost), including model deployment.

Qualifications

• Experience with Python, Java, Scala, or C++
• ML Frameworks & Libraries – XGBoost, Scikit‑learn, Tensor Flow/keras, Hugging face (NLP/NLQ/Gen AI use cases)
• Full-Stack Development
• Performance Optimization
• Data Engineering & Ingestion Frameworks
• Collaboration with Data Science Teams