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Evolutionary Computing Jobs in Boston, MA (NOW HIRING)

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Evolutionary Computing information

See Boston, MA salary details

$11.9K

$62.3K

$103.8K

How much do evolutionary computing jobs pay per year?

As of Jul 18, 2026, the average yearly pay for evolutionary computing in Boston, MA is $62,338.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,300.00 and $75,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced when implementing evolutionary computing algorithms in real-world projects?

One of the main challenges in applying evolutionary computing algorithms is balancing computational cost with solution quality, as these algorithms can be resource-intensive and require careful parameter tuning. Additionally, translating theoretical models into scalable, real-world applications often involves customizing operators and fitness functions to suit specific domains. Collaboration with domain experts is crucial to accurately define objectives and constraints, and ongoing communication with software engineers ensures efficient integration into existing systems.

What are the key skills and qualifications needed to thrive as an Evolutionary Computing Specialist, and why are they important?

To thrive as an Evolutionary Computing Specialist, you need a solid background in computer science, mathematics, and algorithm design, often supported by an advanced degree in a related field. Familiarity with programming languages (such as Python, C++, or Java), machine learning frameworks, and optimization libraries is typically required. Strong analytical thinking, problem-solving abilities, and creativity are crucial soft skills that help in developing innovative solutions. These skills enable specialists to design and implement effective evolutionary algorithms that solve complex computational problems across various domains.

What is the difference between Evolutionary Computing vs Data Scientist?

AspectEvolutionary ComputingData Scientist
Required CredentialsTypically a degree in computer science, AI, or related fields; certifications in AI or machine learningDegree in statistics, computer science, or related fields; certifications in data analysis or machine learning
Work EnvironmentResearch labs, AI development teams, academiaBusiness environments, tech companies, consulting firms
Industry UsageOptimization problems, evolutionary algorithms researchData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

While both roles involve advanced computing techniques, Evolutionary Computing focuses on algorithms inspired by natural selection for optimization, whereas Data Scientists analyze data to extract insights and build predictive models. They often collaborate but serve different primary functions within tech and research industries.

What is evolutionary computing?

Evolutionary computing is a branch of artificial intelligence that uses algorithms inspired by the process of natural selection to solve complex optimization and search problems. These algorithms, such as genetic algorithms, evolve solutions over time by mimicking biological mechanisms like mutation, crossover, and selection. Evolutionary computing is used in various fields, including engineering, economics, and robotics, to find solutions that might be difficult to obtain through traditional methods. It is especially useful for problems where the search space is vast and not easily navigable by conventional algorithms.
What are popular job titles related to Evolutionary Computing jobs in Boston, MA? For Evolutionary Computing jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Evolutionary Computing jobs in Boston, MA look for? The top searched job categories for Evolutionary Computing jobs in Boston, MA are:
Evolutionary Computing jobs near you
Infographic showing various Evolutionary Computing job openings in Boston, MA as of July 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $62,338 per year, or $30 per hour.
Postdoctoral position in AI for Engineering Applications

Postdoctoral position in AI for Engineering Applications

Harvard University

Cambridge, MA • On-site

$67K - $91K/yr

Full-time

Posted yesterday

New

Harvard University rating

8.4

Company rating: 8.4 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

81st of 555 rated colleges and universities

Job description

Position
Details
Title
Postdoctoral position in AI for Engineering Applications
School
Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area
Applied Math
Position Description
The Computational Science and Engineering Laboratory at Harvard University invites applications for postdoctoral position at the interface of scientific Computing and Artificial Intelligence for applications pertaining to fluid mechanics of turbulent and environmental flows starting September 1, 2025, or as soon thereafter as possible. The position is for one year, with the possibility of renewal for two additional years. The candidate will work closely with Professor Petros Koumoutsakos cse-lab.harvard.edu.
Basic Qualifications
Doctoral degree. Applicants background may include studies in: Computational Science, Computer Science, Applied Mathematics, Engineering and Physics.
Additional Qualifications
Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing are desirable. We particularly encourage applicants with expertise in Multi-scale Modeling, Evolutionary Computation, Diffusion models, Reinforcement Learning. The successful candidate will work in a highly collaborative and international environment.
Special Instructions
Contact Information
For further information, please contact petros@seas.harvard.edu.
Contact Email
lreck@seas.harvard.edu
Salary Range
$67,600 - $91,826
Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.
Minimum Number of References Required
2
Maximum Number of References Allowed
4
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