Support EDPR’s global fleet of generating assets by detecting, reporting, and documenting potential future failures in wind turbines, solar panels, BESS, or other electric systems using condition monitoring and data analytics.
Locations (3)
Houston, Texas, United States
British Columbia, Canada
California, United States
Responsibilities
Detect potential failures using EDPR’s corporate condition monitoring tools to analyze operational data
Communicate clear inspection and repair recommendations to the site managers and technicians
Provide remote support to site personnel to ensure recommendations are addressed correctly
Report the results of the inspection feedback and relay decisions of replacing/repairing the component, material, system, etc.
Assess failure types, remaining useful life, and scope of work required based on inspection pictures
Requirements
Bachelor’s degree in engineering (Mechanical or a related field)
Master’s preferred
Nice to have: Familiarity with planetary gearboxes, generators, solar, BESS, and/or power generation and conversion equipment
Nice to have: Familiarity with rotating equipment reliability and lubrication
Nice to have: Familiarity with Python or R software
Design and implement machine learning models and algorithms that power advertiser-facing AI experiences, using generative AI to transform the advertising lifecycle.
Compensation
The base salary range for this position is listed below. ... 149,300.00 - 249,300.00 CAD annually
Responsibilities
Design and implement machine learning models and algorithms that power advertiser-facing AI experiences, ensuring scientific rigor from research through production deployment.
Conduct applied research to extend or invent new approaches for complex advertising problems where no textbook solutions exist, working backwards from advertiser needs.
Collaborate with engineering, product, and science teams to integrate your solutions directly into large-scale production systems serving millions of advertisers.
Analyze experimental results and system performance to identify improvement opportunities, making informed tradeoffs between model complexity, latency, and business impact.
Mentor other scientists, provide peer feedback on research procedures and results, and contribute to the team's scientific roadmap and technical direction.
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