# Senior Machine Learning Engineer

> Amartha · Shenzhen, China (Hybrid) · Full-time · Posted 2026-07-22

**Workplace:** hybrid

**Department:** Tech

## Description

_**About Amartha**_

At Amartha, we empower micro-businesses across Indonesia, enabling growth and equal prosperity. We've supported over 3.5+ million enterpreneurs–mostly women–by disbursing 2 billion USD in funding. As we step into 2026, Amartha is evolving into a technology-driven financial ecosystem, expanding our reach in lending, funding, and payments. Through innovation and digital solutions, we aim to enhance accessibility, streamline processes, and create a seamless user experience.

_**Roles and Responsibilities:**_

-   Design, develop, and productionize ML models for credit scoring, underwriting, fraud detection, collections, and portfolio risk management.
-   Build robust features from customer, transaction, repayment, behavioral, and alternative data.
-   Select and evaluate appropriate algorithms, with emphasis on explainable and high-performing models such as XGBoost.
-   Define offline and online evaluation metrics aligned with lending outcomes and business objectives.
-   Address class imbalance, data leakage, bias, model stability, and changing customer behavior.
-   Build reliable training, validation, deployment, monitoring, and retraining pipelines.
-   Monitor model performance, calibration, drift, fairness, and operational impact in production.
-   Produce clear model documentation and explain decisions to risk, product, engineering, compliance, and business stakeholders.
-   Collaborate with data engineers and software engineers to integrate models into scalable production systems.
-   Conduct experiments and translate model improvements into measurable business outcomes.
-   Explore practical LLM and agentic-AI applications, such as document processing, underwriting assistance, investigation workflows, and internal productivity tools.

## Requirements

-   Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field, or equivalent practical experience.
-   5+ years of ML Engineering or Data Scientist experience
-   Strong foundation in traditional machine learning, including classification, regression, feature engineering, model evaluation, and imbalanced-data handling.
-   Hands-on experience with models such as XGBoost, LightGBM, random forests, and logistic regression.
-   Proficiency in Python, SQL, and ML libraries such as scikit-learn, XGBoost, pandas, and NumPy.
-   Experience deploying, monitoring, and maintaining ML models in production.
-   Understanding of model explainability, drift detection, experiment tracking, and reproducible ML workflows.
-   Knowledge of credit risk, underwriting, fraud detection, customer scoring, or related financial-services use cases.
-   Experience in fintech, digital lending, or microfinance is strongly preferred.
-   Familiarity with cloud platforms, containers, APIs, and data pipelines.
-   Exposure to LLMs, retrieval-augmented generation, prompt engineering, or agentic programming is a plus.

_At Amartha, we are dedicated to creating a workplace that celebrates diversity, ensures equity, and fosters inclusion. We believe that diverse perspectives—shaped by factors such as gender, age, race, ethnicity, education, culture, and life experiences—drive innovation and growth._

_We actively welcome individuals from all backgrounds to join us in building an environment where everyone feels respected, valued, and empowered. Our commitment is to provide equal opportunities and foster a sense of belonging that enables our employees to thrive and make meaningful contributions._

## Apply

[Apply at Amartha](https://apply.workable.com/amartha/j/20E5E2ECA5/apply)

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