Sr Data Scientist , Annapurna Labs, ML Acceleration Power Architecture in , us

Energy Jobline ATTB; Théméricourt; Sur place; EUR 124 000 - 216 000; Plein temps

Résumé du poste

A leading global energy job platform is seeking a skilled Data Scientist to join their Machine Learning Architecture team. The role involves analyzing performance metrics, developing predictive models, and collaborating with cross-functional teams to optimize ML workloads across data centers. The ideal candidate has extensive experience in data querying and statistical modeling, with a focus on energy efficiency. This position offers a competitive salary range of $143,300 to $247,600 per year.

Qualifications

• 5+ years of experience with data querying, scripting, or statistical software.
• 4+ years of data scientist experience.
• Experience with statistical models like multinomial logistic regression.

Responsabilités

• Analyze power consumption and performance metrics across data centers.
• Develop predictive models and identify optimization opportunities.
• Provide data-driven recommendations for server deployments.
• Conduct applied research on ML acceleration technologies.

Connaissances

Data querying (SQL)

Scripting (Python)

Statistical models

Data visualization (AWS QuickSight)

Managing data pipelines

Description du poste

Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide.

We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.

Description

We are seeking a highly skilled Data Scientist to join our Machine Learning Architecture team, focusing on power and performance optimization for ML acceleration workloads across Amazon's global data center infrastructure. This role combines advanced data science techniques with deep technical understanding of ML hardware acceleration to drive efficiency improvements in training and inference workloads at massive scale.

Job Responsibilities

• Data Analysis & Optimization
  • 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
• Strategic Planning & Deployment Guidance
  • 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
• Cross-Functional Collaboration
  • 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
• Research & Development
  • 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

Basic Qualifications

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

Additional Qualifications

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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, or other legally protected status.

Compensation range: $143,300 to $247,600 per year (location dependent). Equity, sign‑on, and additional benefits may also be part of the total compensation package.

Applicants should apply via our internal or external career site. Energy Jobline wishes you the very best of luck in your next career move.