Data Scientist Software Engineering AI/ML

Advanced Micro Devices, Inc•Austin, TX

About The Position

AMD is seeking a Developer / Data Scientist for its product development organization focused on power and performance optimization for client PC platforms. The role combines data science, low-level systems engineering, and algorithm development. The successful candidate will work with engineering and architecture teams to analyze telemetry at scale, tune dynamic optimization algorithms, and help modern PCs adapt to different hardware configurations and real-world usage scenarios. The position involves both detailed data analysis and hands-on software engineering. The role’s findings are expected to inform engineering, leadership, and partner organizations and influence customer experiences across PC populations. The role is not eligible for visa sponsorship.

Requirements

Strong statistical fundamentals and ability to model relationships, quantify uncertainty, and draw rigorous conclusions.
Ability to perform both detailed data analysis and hands-on software engineering.
Experience developing or maintaining software tools; the role primarily uses Python and C.
Ability to communicate complex analytical findings to technical and non-technical audiences.

Nice To Haves

Bachelor’s or Master’s degree in a related discipline.
Familiarity with PC benchmarking tools and methodologies such as Procyon, 3DMark, Cinebench, and BAPCo.
Experience with ML toolchains, workflows, or model deployment.
Experience with Dataiku or similar data science platforms; Dataiku is a strong plus.
Understanding of PC system architecture, hardware abstraction, or platform performance tuning.
Experience integrating algorithms into production environments across varied hardware configurations.

Responsibilities

Analyze power and performance instrumentation, including battery life, thermal behavior, and workload responsiveness.
Conduct investigations ranging from single-system deep dives to statistical studies across hundreds of thousands of devices in the field.
Build, refine, and maintain tools, dashboards, visualizations, and interactive analysis pipelines for identifying trends and anomalies.
Use statistical methods to model relationships, quantify uncertainty, generate insights, and support rigorous conclusions.
Communicate analytical findings clearly to technical and non-technical audiences.
Use industry benchmark data, including Procyon, 3DMark, Cinebench, and BAPCo, to investigate performance outcomes and identify improvements.
Develop and maintain tools, primarily in Python and C, to characterize, optimize, and integrate power/performance algorithms, including ML-based components.
Contribute to the design and tuning of algorithms that dynamically adjust hardware parameters based on system configuration, environment, and user scenarios.
Collaborate with cross-functional teams to integrate algorithms into production environments and partner-facing SDKs.
Implement scalable data pipelines, ML workflows, or validation frameworks.
Contribute to automation, performance measurement workflows, and algorithm validation frameworks.
Participate in performance tuning, quality validation, and continuous improvement of system optimization logic.