Machine Learning Engineer Intern

Job Summary

Branch's ML based underwriting models are core to our business and directly drive business value. Every credit decision, fraud signal, and credit scoring model we deploy has a direct impact on real customers access to capital. We are looking for engineers who want to grow with us, take deep ownership, and have a genuine impact on how ML is built and deployed in production.

We are hiring ML engineering interns to join our ML team in India. This team owns our core credit models, infrastructure, and the tooling that powers them. They also actively research and develop what comes next for ML at Branch for real credit and lending problems.

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making: We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.

Here are some things you'll do

Responsibilities

• Build, maintain, and scale ML infrastructure end-to-end: feature computation pipelines serving real-time predictions at millions of requests per day, and training and deployment pipelines spanning classical and cutting-edge models.
• Build observability and drift monitoring to detect and respond to model degradation in production.
• Evaluate and address selection bias in credit models using techniques from reject inference to deep generative approaches.
• Explore using LLMs/agentic AI to generate features from raw data, automate segment analysis, inform credit and policy exploration, and more.
• Collaborate with credit underwriting, product, and backend teams to build signals from structured and unstructured data that identify creditworthy borrowers and power our underwriting models.

Minimum Requirements

• Have some experience building ML applications that are more than just toy projects. Applications that have real users or an open source project would be a great plus.
• Strong skills in building machine learning models using both structured and unstructured data.
• Strong Python proficiency, including ML libraries (XGBoost, scikit-learn, pandas, numpy) and software engineering fundamentals.
• Experience with SQL and structured data, able to write non-trivial queries for feature extraction and analysis.

Nice to have

• GenAI/LLM experience
  1. Prompt engineering, fine-tuning, or building LLM-powered workflows
  2. Familiarity with agentic system design and using structured LLM outputs.
• Credit risk or lending domain experience
  1. Credit risk modeling or loan underwriting in any market.
  2. Leveraging alternative data sources as predictive signals in emerging markets.
• Experience with Rust or compiled languages
• Curious about new technologies and interested in learning different parts of the technology stack beyond ML when needed.
• Demonstrated fluency with modern AI-assisted development workflows and a point of view on their effectiveness for various use cases.
• Clear, structured written and verbal communication, comfortable operating async effectively.

Core Engineering Expectations

The following describes the traits we expect in our engineers, and reflects instincts developed over years of shipping real software. If you are early in your career, we do not expect you to demonstrate all of it yet - but we do expect a genuine appreciation for why these qualities matter, an honest sense of where you stand against them, and the drive to close the gap.

Engineering craft and judgment

• You balance technical excellence with business and consumer needs. You research and seek opinions to identify the best solution for a problem, not just the first one that comes to mind. You intentionally weigh technical debt, ensuring it is paid down before it compounds.
• You have a deep understanding of web fundamentals, data modeling, and distributed systems. You apply proven design patterns to build modular, scalable solutions and ensure that security, performance, and observability are baked into your work from the outset.

Disclaimer: This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.