Machine Learning Tools Engineer, SIML

As a Machine Learning Tools Engineer, you will: * Design, develop, and maintain core ML infrastructure components (training pipelines, experiment tracking, deployment tooling, and monitoring systems). * Collaborate with ML practitioners to identify pain points and translate them into productized solutions that enhance productivity and reliability. * Build and maintain Python-based SDKs, CLIs, and APIs that simplify how ML engineers interact with compute, data, and models. * Ensure tools are robust, performant, and user-friendly, with strong observability and documentation. * Partner with infrastructure, MLOps, and platform teams to ensure end-to-end system integration and smooth scaling. This is a highly collaborative role that requires curiosity, empathy for users, and a drive to make ML development frictionless. Bachelor’s degree in Computer Science, Engineering, or a related technical field; or equivalent practical experience. 3+ years of experience in software development with strong Python proficiency. Familiarity with machine learning fundamentals and frameworks (e.g., PyTorch, TensorFlow, JAX). Experience with Linux systems, containers (Docker), and version control (Git). Strong debugging, analytical, and problem-solving skills. Comfortable operating at the intersection of research and product, coordinating across teams with competing timelines and technical constraints. Prior experience in an ML platform, infrastructure, or productivity tools team. Experience building internal SDKs, CLIs, or automation frameworks for ML or data workflows. Exposure to distributed training, experiment tracking, or model serving infrastructure. Experience supporting large internal or external developer communities.

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