Principal Software Engineer, ML & Distributed Systems

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About this kind of role

What a Principal Software Engineer, ML & Distributed Systems usually does. The employer's own details are in the listing.

Typically does: A Principal Software Engineer specializing in Machine Learning and Distributed Systems designs, develops, and maintains complex systems that leverage machine learning models at scale. This role involves leading technical projects, mentoring other engineers, and contributing to architectural decisions. Responsibilities often include optimizing performance, ensuring reliability, and implementing robust data pipelines. They may also research and evaluate new technologies to improve existing infrastructure.

Tools and skills: Proficiency in programming languages like Python and Java, experience with distributed computing frameworks (e.g., Spark, Hadoop), cloud platforms (e.g., AWS, Azure, GCP), machine learning libraries (e.g., TensorFlow, PyTorch), and strong understanding of data structures and algorithms is generally expected.

Good fit for: Individuals with extensive experience in software engineering, a deep understanding of machine learning principles, and a passion for building scalable and reliable systems thrive in this role.