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Amartha

P2P lending for women-led MSMEs

Senior Machine Learning Engineer - Tech

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeShenzhen, Guangdong Province, ChinaNo salary listedHybrid

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field, or equivalent practical experience.
  • At least 5 years of Machine Learning Engineering or Data Scientist experience.
  • A strong foundation in traditional machine learning, including classification, regression, feature engineering, model evaluation, and imbalanced-data handling.
  • Hands-on experience with XGBoost, LightGBM, random forests, and logistic regression.
  • Proficiency in Python, SQL, and machine learning libraries such as scikit-learn, XGBoost, pandas, and NumPy.
  • Experience deploying, monitoring, and maintaining machine learning models in production.
  • Understanding of model explainability, drift detection, experiment tracking, and reproducible machine learning workflows.
  • Knowledge of credit risk, underwriting, fraud detection, customer scoring, or related financial-services use cases.
  • Familiarity with cloud platforms, containers, APIs, and data pipelines.

Responsibilities

  • Design, develop, and productionize machine learning 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, emphasizing 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 large language model and agentic artificial intelligence applications, such as document processing, underwriting assistance, investigation workflows, and internal productivity tools.

Desired Qualifications

  • Experience in fintech, digital lending, or microfinance is strongly preferred.
  • Exposure to large language models, retrieval-augmented generation, prompt engineering, or agentic programming is a plus.

About the Company

Amartha

P2P lending for women-led MSMEs

Amartha is a fintech platform in Indonesia that connects micro-entrepreneurs with investors through a peer-to-peer lending marketplace. It funds productive loans for MSMEs, focusing on women-led businesses, using a hybrid model of digital technology plus in-person field agents to support group lending inspired by Grameen Bank. Borrowers access working capital without traditional collateral, supported by a proprietary credit-scoring algorithm that uses machine learning and alternative data to assess creditworthiness of borrowers with no formal credit history. Lenders invest in loans, monitor impact, and earn returns; Amartha aims to improve financial inclusion for the unbanked rural population, empower women, and support sustainable rural economic growth, disbursing over $1.6B to more than 2.5 million women-led businesses as of 2024.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$276M
Headquarters
Jakarta, Indonesia
Founded
2010

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