Remote Software engineering Jobs • MLOps

We are hiring a Senior Machine Learning Engineer to build, ship, and steward production ML systems that power marketing optimisation, forecasting, and decision automation across our verticals. You will own the end‑to‑end ML lifecycle: feature pipelines, training, evaluation, model serving, monitoring, and continuous improvement.

As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy. You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.

As a Staff Engineer, you will support the technical vision and development of ML infrastructure used to enable the end-to-end development and delivery of ML models at Marqeta. You will collaborate closely with Machine Learning Science, Product, and Engineering teams to refine ML development journeys, improve our target state ML architecture and collaborate with our engineering teams to deliver it.

Design and implement the next generation backend ML systems that power the personalized feeds on Reddit. Work closely with ML engineers to design and implement scalable interfaces. Explore new technologies that help grow our ML systems capabilities. Champion and drive engineering processes and best practices. Write efficient, scalable and maintainable code. Mentor ML engineers, fostering a culture of excellence.

We are seeking a Senior Backend Engineer to join the team, with a focus on bridging backend software engineering and applied machine learning. In this role, you’ll build and maintain backend systems that operationalize ML models, collaborate with ML engineers to adapt pre-trained models, and ensure intelligent features run reliably in production environments.

As a Staff Engineer in Machine Learning Infrastructure, you'll drive the technical vision and development of ML infrastructure to enable end-to-end ML model development and delivery at Marqeta. You will collaborate with Machine Learning Science, Product, and Engineering teams to refine ML development journeys and improve our target state ML architecture.

Implement state-of-the-art models and techniques, including deep learning architectures and foundation models. Diagnose model performance issues, analyze sources of error and design strategies to mitigate them. Work with scientific and biological data to contribute to projects in drug discovery, life sciences and healthcare. Design and run experiments, critically evaluate results and communicate findings through clear, data-driven reports.

Designs and builds data infrastructure that supports large-scale feature computation, transformation, and storage. Develops frameworks for batch and event-driven features with a focus on reliability, scalability, and ease of use. Drives improvements in data quality and governance through validation, anomaly detection, drift monitoring, and feature lineage tracking.