Sr Data Scientist , Annapurna Labs, ML Acceleration Power Architecture

Sr Data Scientist , Annapurna Labs, ML Acceleration Power Architecture

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• Analyze power consumption and performance metrics across all Amazon data centers for machine learning acceleration workloads.
• Develop predictive models and statistical frameworks to identify optimization opportunities and performance bottlenecks.
• Create automated monitoring and alerting systems for power and performance anomalies.
• Provide data-driven recommendations for server deployments and capacity planning decisions across Amazon’s global data center network.
• Develop optimization scenarios and business cases to improve capacity delivery efficiency to customers worldwide.
• Support strategic decision-making through comprehensive analysis of power, performance, and cost trade-offs.
• Partner with software engineering teams to optimize ML frameworks, drivers, and runtime systems.
• Collaborate with hardware engineering teams to influence chip design, server architecture, and cooling system optimization.
• Work closely with data center operations teams to implement and validate optimization strategies.
• Conduct applied research on emerging ML acceleration technologies and their power/performance characteristics.
• Develop novel methodologies for measuring and improving energy efficiency in large-scale ML workloads.
• Publish findings and contribute to industry best practices in sustainable ML infrastructure.

• 5+ years of data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab).
• 4+ years of data scientist experience.
• Experience with statistical models such as multinomial logistic regression.

• 2+ years of data visualization using AWS Quick Sight, Tableau, R Shiny, etc.
• Experience managing data pipelines.
• Experience as a leader and mentor on a data science team.

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Compensation: $143,300‑$247,600/year based on location. Equity, sign‑on payments, and other benefits may be provided as part of a total compensation package. This position will remain posted until filled. Applicants should apply via our internal or external career site.