About the Role:

We are seeking a Machine Learning Software Engineer to join Fetch’s Scan, Match & Catalog team. This role sits at the intersection of applied machine learning, data engineering, and production systems, with a focus on improving receipt understanding, product matching, and catalog enrichment at scale. You will partner closely with product, operations, and platform teams to deliver ML-driven automation, including computer vision and OCR pipelines, LLM-based workflows, and scalable ML services. This is a high-impact opportunity to help shape Fetch’s Scan-to-Catalog foundation and significantly increase automation, quality, and match coverage across the platform.

Role Responsibilities: 

Build and scale ML models across the scan, match and catalog pipeline, supporting receipt understanding, product matching, and catalog enrichment. Implement and iterate on active learning strategies, including data sampling, error-driven retraining, and human-in-the-loop workflows. Leverage LLMs to reduce model training and annotation effort, including synthetic data generation, assisted labeling, weak supervision, and error analysis. Own ML experimentation, evaluation, and production inference for assigned SMaC components. Collaborate with product, data, and platform partners to translate quality gaps into ML improvements. Maintain high standards for model performance, reliability, and data quality. Use AI tools to accelerate your work, including: Designing features and validating ideas with ChatGPT & Claude sandboxes. Leveraging AI for code generation and technical prototyping. Using AI assistants for systems architecture diagramming and design validation.

Minimum Requirements:

5+ years experience in software engineering, with production-level coding experience. Strong proficiency in Python for ML development, with working knowledge of Go, and hands-on experience deploying models into production systems. Experience with AWS technologies and distributed systems. Practical experience applying LLMs to reduce training and annotation effort, including assisted labeling, synthetic data generation, weak supervision, or error analysis. 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.

Preferred Requirements:

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field. Equivalent practical experience considered in lieu of degree. Familiarity with AI tools and frameworks like AWS Bedrock, Langchain, vector databases, or similar AI orchestration technologies. Experience with machine learning workflows and large language models (LLMs). Familiarity with orchestrating ML-driven actions in high-complexity or high-throughput environments. Hands-on experience with computer vision and OCR, such as receipt/document parsing, layout-aware modeling, or image-based ML pipelines. Experience working in small, fast-moving, cross-functional teams.

This is a full-time role that can be held from one of our US offices or remotely in the United States.

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is [INSERT RANGE]. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.