ML Platform Engineer |Remote

Role Responsibilities

• Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible programmatic workflows using Python and command-line tools.
• Optimize training or inference for latency, throughput, memory usage, and hardware utilization.
• Diagnose numerical instability, incorrect tensor behavior, memory bottlenecks, distributed-system failures, and performance regressions.

Requirements

• A master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
• Strong professional or research experience in machine learning.
• Practical proficiency with Python.
• Meaningful experience with at least two relevant ML frameworks, libraries, or inference tools.
• Ability to debug ML systems beyond surface-level API usage.