> Markdown version of [/jobs/ext/4638371-software-engineer-infrastructure](https://www.wearedevelopers.com/jobs/ext/4638371-software-engineer-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - Infrastructure - **Company:** Baseten, Inc - **Location:** New York, NY, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Distributed Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, Performance Tuning, AI Infrastructure, Data Logging, Scripting, Reliability of Systems, Containerization, Kubernetes, Information Technology, Machine Learning Operations - **Published:** November 8, 2026 - **Apply:** https://www.juju.com/job/28_25303_fb996a6167406d8c03ccdb6a59a6105e ## About the Role * Bachelor's degree or higher in Computer Science or related field * Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus * Working knowledge of Kubernetes and containerization * Basic understanding of machine learning concepts and model serving * Familiarity with distributed systems concepts * Experience with basic monitoring and logging tools * Interest in ML/AI infrastructure and willingness to learn * Strong collaboration and communication skills ## Description As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance., * Develop infrastructure components for our ML inference platform using Python and Go * Implement and maintain Kubernetes deployments for model serving * Contribute to our inference orchestration layer for model deployments * Build and enhance monitoring systems for model performance metrics * Implement efficient resource management solutions for ML workloads * Support infrastructure automation to improve ML deployment workflows * Work closely with team members to implement technical solutions * Help balance performance optimization with system reliability * Participate in technical discussions around infrastructure improvements * Learn and apply infrastructure best practices