Applied ML Engineer building machine learning systems for Paramount's entertainment services. Implementing model integrations and data pipelines in a dynamic environment.
Responsibilities
Implement machine learning systems, including model integrations, data pipelines, retrieval systems, evaluation instrumentation, and service layers.
Translate technical direction into modular, maintainable codebases with clear interfaces.
Deliver working artifacts at defined milestones, including code, configuration, tests, and documentation.
Iterate on systems based on evaluation results, domain feedback, and integration requirements.
Refine performance, usability, and functionality within the scope of the system being built.
Implement evaluation hooks, metrics, and instrumentation defined by the ML Behavior Systems team.
Ensure systems can be tested against defined benchmarks and quality standards.
Build systems using ML Platform & Operations infrastructure for training, inference, and deployment.
Ensure compatibility with platform services, APIs, and constraints.
Design outputs as modular components with stable interfaces.
Include configuration controls, observability hooks, and error handling required for integration.
Requirements
4+ years of software engineering experience in backend, systems, or ML-adjacent environments
2+ years hands-on ML implementation.
Proficient programming skills, particularly in Python, and experience building APIs or services.
Working knowledge of machine learning systems, including model integration, evaluation, and debugging.
Experience building end-to-end systems from unclear requirements to working software.
Ability to operate in dynamic, iterative development environments.
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