About Artajasa

PT Artajasa Pembayaran Elektronis (ARTAJASA) is one of Indonesia's leading payment infrastructure providers, delivering secure, reliable, and high-availability electronic transaction services for banks and financial institutions. Operating mission-critical systems 24/7, ARTAJASA continuously leverages advanced technologies, including AI and machine learning, to strengthen security, drive operational efficiency, and foster innovation across the national digital payment ecosystem.

About the Role

We are seeking a talented AI/ML Engineer to design and implement scalable machine learning solutions across a wide range of critical business use cases, including fraud detection, biometric authentication, and anomaly detection. This role will play a pivotal part in building end-to-end AI capabilities, from model development through to production deployment, within a secure, high-performance environment.

Key Responsibilities

Design, develop, and deploy AI/ML solutions for high-impact use cases such as fraud detection, biometric face recognition, predictive analytics, and anomaly detection.
Build and manage end-to-end machine learning pipelines, including data preparation, feature engineering, model training, evaluation, deployment, and monitoring (MLOps).
Develop and implement Generative AI solutions, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) for knowledge management and process automation.
Conduct research and evaluation of emerging AI technologies (e.g., computer vision, biometric intelligence, and anomaly detection).
Collaborate closely with product, engineering, and operations teams to translate complex business requirements into scalable AI solutions.
Perform rigorous experimentation, model tuning, and optimization to enhance performance, accuracy, and efficiency.
Document solution architecture, models, and pipelines while supporting effective knowledge transfer to internal teams.

Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field.
Minimum 2–5 years of experience in AI/ML development or related roles.
Strong understanding of machine learning and deep learning concepts, including model development, training pipelines, hyperparameter tuning, and MLOps practices.
Experience with Generative AI, LLM-based systems, RAG architecture, embeddings, and vector databases.
Familiarity with data engineering concepts (ETL/ELT pipelines, data warehouse/lake); experience with stream processing (e.g., Kafka) is a plus.
Hands-on experience with containerization (Docker, Kubernetes) and cloud platforms is an advantage.
Proficiency in Python is required; experience with Go or Java is a plus.
Experience working with SQL/NoSQL databases (e.g., PostgreSQL, Oracle, MongoDB, Elasticsearch, Redis).
Understanding of data security principles, especially in financial services or payment systems, is preferred.
Strong analytical thinking, problem-solving skills, and ability to work collaboratively in a cross-functional environment.