Machine Learning Engineer, Infrastructure
ML6
- San Francisco, California, United States
- San Francisco, California, United States
About
Design, build, and optimize scalable ML systems and data pipeline infrastructure that power AI-driven product capabilities. Develop and maintain production-grade training, evaluation, experimentation, and model serving frameworks. Partner closely with applied ML engineers to enable efficient iteration, deployment, and monitoring of models in production. Write high-quality, maintainable, and well-tested code across backend and infrastructure layers. Improve reliability, observability, and performance of distributed ML workflows in a fast-growing environment. Collaborate cross-functionally with product and engineering teams to solve complex AI challenges. Contribute to engineering culture through mentorship, technical leadership, and best practice development. What You'll Need To Be Successful:
2-5 years of professional software engineering experience. Bachelor's degree in Computer Science, Mathematics, Engineering, or a related technical field. Demonstrated experience designing and shipping production systems, ideally within AI/ML infrastructure (pipelines, model training, serving systems, experimentation platforms, etc.). Strong programming skills in languages such as Python, Go, Java, or C++. Solid understanding of distributed systems, scalability, and performance optimization. Comfort operating in a fast-paced, highly collaborative environment. Ownership mindset with the ability to independently drive both tactical execution and longer-term infrastructure improvements. Experience with, or strong interest in, generative AI and large-scale machine learning systems.
Languages
- English
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