Software Engineer - Machine Learning

permanent

Fully Remote

Only accepting applications from: United States

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 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 while contributing to the larger AI & Data organization.
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 applications in production environments.
Strong collaboration and communication skills, with the ability to explain technical concepts to diverse stakeholders.

Experience

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 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 preferred.
Experience with machine learning workflows and large language models.
Background in fraud detection, automation, or systems designed for revenue protection.
Familiarity with orchestrating ML actions in high-complexity environments.
Previous experience working in small, fast-moving, cross-functional teams.

Equity: We offer employees equity in Fetch, so that everyone can benefit from Fetch’s growth.
401k Match: Dollar-for-dollar match up to 4%.
Benefits for humans and pets: We offer comprehensive medical, dental and vision plans for everyone including your pets.
Continuing Education: Fetch provides ten thousand per year in education reimbursement.
Employee Resource Groups: Take part in employee-led groups that foster a diverse and inclusive workplace.
Paid Time Off: Flexible PTO, 9 paid holidays, and a year-end week-long break.
Robust Leave Policies: 20 weeks of paid parental leave for primary caregivers and 14 weeks for secondary caregivers.
Calvin Care Cash: $2,000 incentive for new family members.
Flexible Work Environment: Work from one of our offices or fully remotely from anywhere in the US.