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Theoretical Computer Science Jobs in California (NOW HIRING)

Apex Informatics

Computer Vision Engineer V

Sunnyvale, CA · On-site

$132K - $156K/yr

... computer science or equivalent relevant experience. • 5+ years of experience designing and ... Preferred Qualification: • MS or PhD in EE/CS • Theoretical knowledge in the field of computer ...

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Theoretical Computer Science information

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$10.9K

$125K

$168.8K

How much do theoretical computer science jobs pay per year?

As of Aug 12, 2026, the average yearly pay for theoretical computer science in California is $124,954.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,800.00 and $151,000.00 per year, depending on experience, location, and employer.

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.

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 jobs can you do with theoretical computer science?

Theoretical computer science graduates can pursue roles such as research scientist, algorithm engineer, cryptographer, or data scientist. These positions often require strong analytical skills, knowledge of algorithms, and programming proficiency in languages like Python or C++, with opportunities in academia, tech companies, and research institutions.

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 the most commonly searched types of Theoretical Computer Science jobs in California? The most popular types of Theoretical Computer Science jobs in California are:
What are popular job titles related to Theoretical Computer Science jobs in California? For Theoretical Computer Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Theoretical Computer Science jobs in California look for? The top searched job categories for Theoretical Computer Science jobs in California are:
What cities in California are hiring for Theoretical Computer Science jobs? Cities in California with the most Theoretical Computer Science job openings:
Theoretical Computer Science jobs near you
Infographic showing various Theoretical Computer Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $124,954 per year, or $60.1 per hour.

Principal / Staff Applied Research Scientist

Snowflake

Menlo Park, CA • On-site

$236K - $339K/yr

Full-time

Re-posted 12 days ago

Job description

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset - who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
Snowflake's Data Engineering organization builds the platform that ingests, transforms, and stores data for modern lakehouse architectures - powering billions of queries, DML, and DDL operations with industry-leading price-performance. We lead the industry's shift to open data lakes through our work on Iceberg and Polaris, and we deliver capabilities like Snowpark, Dynamic Tables, cross-region replication, time travel, and zero-copy cloning at enterprise scale.
We are investing in a new line of applied research - building toward verified data infrastructure and trustworthy data systems - that brings formal methods, automated reasoning, and modern AI techniques to bear on the hardest problems in our distributed systems and developer tooling. The goal is to improve correctness, reliability, and engineering velocity at a scale very few platforms operate at. We're hiring at both the Staff and Principal level; we'll calibrate the offer to the candidate's experience and scope of impact.
What you'll do
  • Lead research projects that apply formal methods, program analysis, automated reasoning, and AI-driven techniques (including code generation and modeling) to real problems in our cloud data platform.
  • Translate research ideas into prototypes, then into shipped capabilities that move concrete business metrics - quality, velocity, reliability, and operational performance at scale.
  • Partner closely with engineering leaders, product managers, and key customers to identify high-leverage opportunities and turn them into deliverables.
  • Influence the engineering and product roadmap; advise leaders on which research directions are pragmatic and which are not.
  • Train and uplevel engineering teams on new methods, and scale those methods across the organization.
  • Maintain expertise at the frontier of the field through publications, conference participation, open-source contributions, and patent filings.
What we're looking for
  • PhD (or equivalent research experience) in Computer Science or a closely related field.
  • Depth across the areas this role sits at the intersection of:
    • Formal methods - e.g., model checking, theorem proving, SAT/SMT, program verification, type systems, or program analysis.
    • Distributed systems - designing, reasoning about, or verifying large-scale concurrent and distributed systems.
    • Software engineering - strong fundamentals; able to go from a research idea to production-quality code in collaboration with engineering teams.
    • AI / ML - practical experience applying modern ML, including LLMs, to systems problems such as code generation, synthesis, or automated reasoning.
  • 8+ years applying theoretical computer science to large-scale software systems - ideally cloud data platforms, distributed systems, or developer infrastructure.
  • Demonstrated ability to drive company-level initiatives in partnership with engineering and product leadership. (Weighted more heavily for Principal-level candidates.)
  • Track record of technical contribution to the field - publications, open-source work, patents, or comparable evidence of impact.
  • Comfortable in a fast-paced, ambiguous environment where impact is measured by what ships.
About working here
Every Snowflake employee is expected to follow the company's confidentiality and security standards for handling sensitive data, and to keep customer information secure and confidential as an essential part of their duties.
Snowflake is growing fast, and we're scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

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