Machine Learning Engineer

• Design, train and productionise supervised, unsupervised and deep-learning models that power fraud detection, risk scoring and personalised client experiences.
• Build repeatable ML pipelines in Python (TensorFlow / PyTorch / scikit-learn) and Java/Scala, orchestrated in Vertex Al, Azure ML and on-prem GPU clusters.
• Implement full-cycle MLOps-version control, automated testing, CI/CD, model registry, drift monitoring and rollback-using Git/Bitbucket, Terraform, Docker and Kubernetes (GKE ).
• Serve low-latency inference via containerised micro-services and streaming engines (Flink, Spark Structured Streaming, Pub/Sub / Kafka).
• Engineer and manage a cross-cloud feature store, integrating BigQuery and on-prem RDBMS to guarantee consistent training/serving features.
• Conduct robust experimentation (A/B, champion-challenger) and hyper-parameter tuning to optimise model performance and business KPIs.
• Embed responsible-AI controls-bias detection, explainability, encryption, role-based access-aligned with UU PDP & OJK AI governance.
• Produce audit-ready documentation, model cards, and lineage artifacts for regulators and internal risk committees.
• Partner with product, data engineering and compliance teams to translate complex ML outputs into actionable insights and secure APIs.
• Track emerging techniques (LLMs, Gen AI, vector databases) and recommend adoption paths that fit latency, cost and compliance constraints.

• Bachelors degree in Computer Science, Information Technology, or related field.
• 3-5 years of experience building and deploying ML solutions at scale (financial services experience a plus).
• Advanced Python and strong Java/Scala skills; expert in SQL and big data pipelines.
• Hands-on with Vertex AI, BigQuery ML, and on-premise GPU or Hadoop environments.
• Proven MLOps expertise (GitOps, CI/CD, Docker/K8s, Terraform, Prometheus/Grafana).
• Solid foundation in statistics, model evaluation, and experimental design.
• Experience with privacy-preserving ML and ethical AI aligned with Indonesian regulatory frameworks.
• Familiarity with real-time model deployment via Spark, Flink, REST/gRPC endpoints.
• Strong communication skills to bridge data science with stakeholders across the business.

Information :

• Company : Bumi Amartha Teknologi Mandiri
• Position : Machine Learning Engineer
• Location : Jakarta Pusat
• Country : ID