Software Engineer - Machine Learning

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full-time

Posted on: 9/25/2025

Origin: • 🇺🇸 United States • Alabama, Illinois, Wisconsin

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JuniorMid-Level

AWSDistributed SystemsGoJavaMicroservices

About the role

Develop scalable backend services and microservices in Java or Go to support ML-driven orchestration.
Build and optimize data pipelines and infrastructure to support event-driven, async, and long-running ML processes.
Partner with engineering teams to automate workflows, integrate models, and ensure revenue protection.
Educate internal stakeholders on ML-driven decision-making and create transparent, traceable systems for fraud management.
Drive automation and orchestration of workflows across fraud, billing, and manual operations teams.
Leverage AI-assisted development tools (e.g., GitHub Copilot, ChatGPT) to accelerate prototyping, code generation, debugging, and documentation.
Evaluate and integrate AI-powered solutions into workflows to improve productivity, model experimentation, and system efficiency.
Collaborate within a small cross-functional team (PM, ML Engineer, BE Engineer) while contributing to the larger AI & Data org.
Champion best practices in software engineering, code quality, testing, and deployment of ML/LLM solutions.
Design, build, and deploy machine learning models and large language model (LLM) applications in production environments.
Strong collaboration and communication skills, with the ability to explain technical concepts to diverse stakeholders.

2+ years experience in software engineering, with production-level coding experience.
Proficiency in Java or Go, with a strong background in microservices and coupled architectures.
Exposure to machine learning workflows or large language models (LLMs) is a plus, but not required.
Experience with AWS technologies and distributed systems.
Working knowledge of Flink or equivalent data/stream processing frameworks.
Solid understanding of event-driven and async architectures, including long-running processes.
Strong engineering mindset with the ability to deliver reliable, maintainable, and scalable systems.
Experience with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, or similar) to improve development efficiency and code quality.
Ability to critically evaluate AI-generated outputs, with strong debugging and problem-solving skills to validate correctness.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Equivalent practical experience considered in lieu of degree.