Engineer Numerical Optimization information
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$43.12 is the 25th percentile. Wages below this are outliers.
$40.63 - $44.36
38% of jobs
The median wage is $47.81 / hr.
$44.36 - $48.10
14% of jobs
$48.10 - $51.84
0% of jobs
$51.84 - $55.57
0% of jobs
$55.57 - $59.31
0% of jobs
$59.31 - $63.05
0% of jobs
$63.05 - $66.78
0% of jobs
$66.78 - $70.52
16% of jobs
$72.51 is the 75th percentile. Wages above this are outliers.
$70.52 - $74.26
16% of jobs
$74.26 - $77.99
10% of jobs
$77.99 - $81.73
7% of jobs
How much do engineer numerical optimization jobs pay per hour?
As of Sep 10, 2026, the average hourly pay for engineer numerical optimization in the United States is $59.65, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $73.56 per hour, depending on experience, location, and employer.
An Engineer Numerical Optimization specializes in developing and applying mathematical algorithms to solve complex engineering problems efficiently. Their work often involves designing, implementing, and improving optimization methods to enhance system performance, reduce costs, or achieve specific technical objectives. They collaborate with multidisciplinary teams to model problems, run simulations, and analyze data, ensuring that solutions are both practical and computationally feasible. This role is critical in industries such as aerospace, automotive, finance, and energy where optimal solutions can provide significant competitive advantages.
To excel as an Engineer Numerical Optimization, you need a strong background in mathematics, optimization algorithms, and programming, usually supported by a degree in engineering, mathematics, or computer science. Familiarity with tools such as MATLAB, Python (with libraries like SciPy or NumPy), and optimization software (e.g., Gurobi, CPLEX) is typically required. Strong problem-solving skills, attention to detail, and effective collaboration are essential soft skills in this field. These competencies enable engineers to devise efficient solutions for complex optimization problems, improving performance and decision-making in various industries.
Engineers specializing in numerical optimization often work closely with multidisciplinary teams, including software engineers, data scientists, and domain experts. They contribute by designing and implementing optimization algorithms that enhance system performance or solve complex engineering problems. Collaboration usually involves regular meetings to discuss requirements, share progress, and integrate optimization solutions into larger systems. Effective communication and teamwork are essential, as these engineers translate mathematical models into practical applications that align with project goals.
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