Power Electronics Machine Learning Engineer information
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$49.8K - $58.5K
5% of jobs
$64.2K is the 25th percentile. Wages below this are outliers.
$58.5K - $67.3K
26% of jobs
$67.3K - $76.1K
7% of jobs
The median wage is $84.9K / yr.
$76.1K - $84.9K
9% of jobs
$84.9K - $93.6K
9% of jobs
$93.6K - $102.4K
16% of jobs
$103.1K is the 75th percentile. Wages above this are outliers.
$102.4K - $111.2K
6% of jobs
$111.2K - $120K
7% of jobs
$120K - $128.7K
5% of jobs
$128.7K - $137.5K
6% of jobs
How much do power electronics machine learning engineer jobs pay per year?
As of Sep 11, 2026, the average yearly pay for power electronics machine learning engineer in the United States is $88,896.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $109,500.00 per year, depending on experience, location, and employer.
A Power Electronics Machine Learning Engineer combines expertise in electrical engineering, specifically power electronics, with machine learning techniques to develop smarter, more efficient electronic systems. They work on optimizing the performance of devices such as inverters, converters, and motor drives by applying data-driven algorithms. Their role may involve tasks like predictive maintenance, system modeling, anomaly detection, and control optimization, often using real-time sensor data. This intersection of disciplines is increasingly important for modern applications in renewable energy, electric vehicles, and industrial automation.
To thrive as a Power Electronics Machine Learning Engineer, you need a solid grounding in electrical engineering, power electronics, and machine learning, typically backed by a relevant degree and experience in both hardware and software domains. Familiarity with simulation tools (such as MATLAB/Simulink), programming languages (like Python), and machine learning frameworks (such as TensorFlow or PyTorch) is commonly required. Strong problem-solving skills, effective communication, and the ability to collaborate across multidisciplinary teams set outstanding candidates apart. These skills and qualifications are crucial for designing innovative solutions that leverage AI to optimize power electronic systems and drive technological advancements.
Power Electronics Machine Learning Engineers often work closely with hardware engineers, embedded software developers, and data scientists to integrate machine learning algorithms into power electronic systems. Collaboration involves regular meetings to align on system requirements, data collection strategies, and model deployment. These engineers also coordinate with testing and validation teams to ensure models perform reliably under real-world operating conditions, fostering a multidisciplinary environment that enhances innovation and problem-solving.
What are popular job titles related to Power Electronics Machine Learning Engineer jobs?
For Power Electronics Machine Learning Engineer jobs, the most frequently searched job titles are:
