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$11K

$126.6K

$171K

How much do theoretical computer science jobs pay per year?

As of Sep 10, 2026, the average yearly pay for theoretical computer science in the United States is $126,612.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,000.00 and $153,000.00 per year, depending on experience, location, and employer.

What is a theoretical computer science?

A Theoretical Computer Science job focuses on studying the fundamental principles of computation, algorithms, complexity, and mathematical models of computing. Professionals in this field work on problems related to computational efficiency, cryptography, machine learning theory, and formal methods. They often conduct research in academia, develop new algorithms, or contribute to cutting-edge technology in industry. These roles typically require strong mathematical skills and expertise in logic, discrete mathematics, and algorithm design.

What are typical responsibilities for someone working in theoretical computer science?

Theoretical Computer Science professionals often spend their days conducting original research, developing new algorithms, and analyzing computational problems from a mathematical perspective. They may collaborate closely with other researchers in interdisciplinary teams, attend academic conferences, and contribute to scholarly publications. While much of the work is individual and highly focused, regular interaction with collaborators and the broader academic community is common. This role can also involve mentoring students and engaging in peer review, making it both intellectually stimulating and highly collaborative.

What are the key skills and qualifications needed to thrive in theoretical computer science, and why are they important?

To thrive in Theoretical Computer Science, a strong background in mathematics, algorithms, and computational theory is essential, usually backed by an advanced degree such as a master's or PhD in computer science or a related field. Familiarity with formal verification tools, mathematical modeling software, and programming languages like Python or C++ is often required. Critical thinking, analytical reasoning, and effective written communication are standout soft skills for this role. These competencies are vital for developing rigorous proofs, articulating complex concepts, and contributing meaningful insights to the field.

Is theoretical computer science useful?

Theoretical computer science is useful for understanding fundamental principles of algorithms, computation, and data structures, which underpin many practical applications in software development, cryptography, and artificial intelligence. It provides a strong foundation for roles involving research, algorithm design, and advanced problem-solving, often requiring skills in mathematics and programming languages. This knowledge can lead to careers in academia, industry research, and technology innovation.

What jobs can you do with theoretical computer science?

Theoretical computer science graduates can pursue roles such as research scientists, algorithms engineers, cryptographers, and data scientists. These positions often require strong analytical skills, programming knowledge, and understanding of computational complexity and algorithms. They are commonly found in academia, technology companies, cybersecurity firms, and research institutions.
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Theoretical Computer Science jobs near you
Infographic showing various Theoretical Computer Science job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 81% Physical, 1% Hybrid, and 18% Remote job distribution, with an average salary of $126,612 per year, or $60.9 per hour.

Software Engineer Intern - Generalist

Fremont, CA • On-site

F-Prime Capital
Investment Clubs and Venture Capital Companies • 11 - 50 employees
Learn more about F-Prime Capitalexternal

$7.0K - $10K/mo

Other

Posted 23 days ago

Job description

Responsibility
  • Design and implement algorithms and evaluation metrics to drive core AI decision-making.
  • Build scalable data pipelines and toolchains for large-scale data ingestion, batch processing, and evaluation.
  • Design system-level evaluation metrics, testing frameworks, and simulation environments across business components.
  • Strong programming skills in C/C++, Python, and software design
  • Strong foundation in mathematics and theoretical computer science, such as linear algebra, calculus, graph theory, computational geometry, combinatorial optimization algorithms, stochastic processes, and complexity analysis.
  • Possessing solid engineering discipline, or demonstrating strong interest and potential in building large-scale systems, with the ability to maximize performance while keeping complexity and cost to a minimum.
  • Pursuing a BS/MS or Ph.D in Computer Science or a related field
  • Experience in large data set processing and familiarity with real time systems
  • Solid experience in a fast-paced and structured engineering environment
  • Full stack experience including both front end and back end is preferred
  • Statistics analysis experience is preferred
Note
  • The position is rolling-based and can start anytime.
  • This position is fully onsite in Fremont, at least 3 months.
Compensation
  • Master: $7000/month
  • PhD: $10,000/month

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