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Open Source Research Jobs in California (NOW HIRING)

Goodfire

Research Scientist

San Francisco, CA · On-site

Preferred : • Experience leading research or contributing to open-source codebases. • Familiarity with interpretability, alignment, or safe model development. • Experience in startup or fast ...

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$20.6K

$97.7K

$176.8K

How much do open source research jobs pay per year?

As of Aug 12, 2026, the average yearly pay for open source research in California is $97,679.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,857.00 and $137,092.00 per year, depending on experience, location, and employer.

What is an open source research?

An Open Source Research job involves gathering, analyzing, and interpreting publicly available data to support decision-making, investigations, or intelligence efforts. This can include examining online publications, social media, government records, and other freely accessible sources. Professionals in this field may work in cybersecurity, journalism, law enforcement, or corporate intelligence. Strong analytical skills, attention to detail, and an understanding of digital tools are essential for success in this role.

What are some of the typical challenges faced by professionals in open source research roles?

Professionals in open source research often encounter challenges such as verifying the authenticity and credibility of information found online, managing large volumes of data, and keeping up with rapidly evolving digital tools and platforms. They may need to navigate language barriers, misinformation, and changing privacy regulations depending on the geographic focus of their research. The work can require a careful balance between thorough investigation and timely reporting. To succeed, researchers often collaborate with analysts, subject matter experts, and cross-functional teams to ensure findings are actionable and reliable.

What are the key skills and qualifications needed to thrive in open source research?

To thrive in Open Source Research, you need strong analytical abilities, attention to detail, and a background in research methodologies, typically supported by a degree in international relations, intelligence studies, or a related field. Familiarity with research databases, online investigative tools, and sometimes certifications like OSINT (Open Source Intelligence) training are valuable. Effective communication, critical thinking, and perseverance are essential soft skills to excel in this field. These skills ensure accurate collection, assessment, and presentation of publicly available information for informed decision-making.

What are the most commonly searched types of Open Source Research jobs in California? The most popular types of Open Source Research jobs in California are:
What are popular job titles related to Open Source Research jobs in California? For Open Source Research jobs in California, the most frequently searched job titles are:
What job categories do people searching Open Source Research jobs in California look for? The top searched job categories for Open Source Research jobs in California are:
What cities in California are hiring for Open Source Research jobs? Cities in California with the most Open Source Research job openings:
Open Source Research jobs near you
Infographic showing various Open Source Research job openings in California as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, 2% Temporary, and 2% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $97,679 per year, or $47 per hour.

Founding Research Engineer, AI-Driven Compilation

SF Tensor

San Francisco, CA • On-site

Full-time

Re-posted 22 days ago

Job description

Job Summary:
SF Tensor is a company focused on AI and high-performance computing, aiming to eliminate bottlenecks in software and infrastructure. The Founding Research Engineer will develop reinforcement learning systems for compiler optimization, exploring large optimization spaces and improving compilation quality over time.
Responsibilities:
• Design and implement RL-based systems for compiler optimization (things like phase ordering, tile size selection, scheduling decisions, and fusion strategies)
• Build agentic compilation systems that use LLMs to reason about code and apply transformations
• Develop reward models and the training infrastructure for our compiler optimization agents
• Create representations and embeddings of compiler IR that work well for learned optimization
• Design feedback loops that let the system improve continuously from real production workloads
• Work closely with compiler engineers to integrate these learned components into the full compilation pipeline
• Run experiments, dig into the results, and iterate on what works
• Publish and open-source research when it makes sense
Qualifications:
Required:
• Strong background in reinforcement learning, with hands-on experience training RL agents on real problems
• Experience building LLM agents, tool use, or other agentic systems
• Good familiarity with GPU programming concepts
• Solid proficiency in Python and PyTorch or JAX
• Ability to design and run solid, rigorous experiments
Preferred:
• Experience with ML compiler stacks (XLA, TVM, Triton, MLIR)
• Experience with RLHF, reward modeling, or preference learning
• Background in combinatorial optimization or program synthesis
• Publications or clear research contributions in RL, learned optimization, or ML for systems
• Familiarity with compiler concepts (IR, optimization passes, code generation)
• Familiarity with GPU performance optimization
• Prior work on learned indexing, learned query optimization, or similar ML-for-systems projects
Company:
The San Francisco Tensor Company is reinventing the software and infrastructure stack for modern AI and HPC. Founded in 2025, the company is headquartered in San Francisco, USA, with a team of 2-10 employees. The company is currently Early Stage.

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