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Software Engineer Research Assistant Jobs in California

Ayar Labs

Sr. Engineer, Research Software

San Jose, CA · On-site

$170K - $192K/yr

Sr. Engineer, Research Software Location: San Jose, CA (on-site) Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As pioneers of co-packaged optics (CPO), we are ...

Ayar Labs

Sr. Engineer, Research Software

San Jose, CA · On-site

$170K - $192K/yr

Sr. Engineer, Research Software Location: San Jose, CA (on-site) Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As pioneers of co-packaged optics (CPO), we are ...

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Software Engineer Research Assistant information

What skills and qualifications are needed to thrive as a software engineer research assistant?

To thrive as a Software Engineer Research Assistant, you need a solid background in computer science fundamentals, programming languages such as Python or Java, and a related degree or ongoing coursework. Familiarity with version control systems like Git, data analysis libraries, and research tools such as MATLAB or TensorFlow is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate with research teams and convey technical findings clearly. These competencies are crucial for contributing to innovative research projects, ensuring reliable results, and supporting the advancement of technology.

What does a software engineer research assistant do?

A Software Engineer Research Assistant supports research projects by developing, testing, and maintaining software tools and applications. They often collaborate with researchers and engineers to implement experimental algorithms, analyze data, and document findings. The role may involve coding, debugging, and adapting software to meet the needs of specific research objectives. Additionally, they help ensure that research code is efficient, reproducible, and well-documented for future use.

How does a software engineer research assistant typically collaborate with engineering and research teams?

Software Engineer Research Assistants often serve as a bridge between software development and research teams, translating research concepts into functional prototypes or tools. They regularly participate in joint meetings, contribute to code reviews, and align their tasks with the goals of both groups. Effective communication skills are essential, as they need to understand academic research requirements while adhering to engineering best practices. This collaborative environment offers exposure to cutting-edge technology and the opportunity to contribute to innovative projects.
What are the most commonly searched types of Software Engineer Research jobs in California? The most popular types of Software Engineer Research jobs in California are:
What are popular job titles related to Software Engineer Research Assistant jobs in California? For Software Engineer Research Assistant jobs in California, the most frequently searched job titles are:
What job categories do people searching Software Engineer Research Assistant jobs in California look for? The top searched job categories for Software Engineer Research Assistant jobs in California are:
What cities in California are hiring for Software Engineer Research Assistant jobs? Cities in California with the most Software Engineer Research Assistant job openings:
Software Engineer Research Assistant jobs near you
Infographic showing various Software Engineer Research Assistant job openings in California as of August 2026, with employment types broken down into 1% Internship, 85% Full Time, 9% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Software Engineer, Research Acceleration

Thinking Machines Lab

San Francisco, CA • On-site

$350K - $475K/yr

Other

Medical, Dental, Vision, PTO

This job post has expired today. Applications are no longer accepted.

Job description

About the Role

We're looking for engineers to build the libraries and tools that accelerate research at Thinking Machines. You'll own internal infrastructure - evaluation libraries, RL training libraries, experiment tracking platforms - and build systems that compound research velocity over time.

This is a collaborative role. You will work directly with researchers to identify bottlenecks and pain points. Success means researchers trust your systems to just work and find them a delight to use.

What You'll Do
  • Design, build, and operate research infrastructure including evaluation frameworks, RL training systems, experiment tracking platforms, visualization tools, and shared utilities.
  • Develop high-throughput, scalable pipelines for distributed evaluation, reward modeling, and multimodal assessment.
  • Build systems for reproducibility, traceability, and robust quality control across research experiments and model training runs. Implement monitoring and observability.
  • Partner directly with researchers to identify bottlenecks and unlock new capabilities. Own research tooling like a product manager, proactively seeking feedback and tracking adoption.
  • Collaborate with infrastructure, data, and product teams to integrate tools across the technical stack.
Skills and Qualifications

Minimum qualifications:

  • Bachelor's degree or equivalent experience in computer science, engineering, machine learning, or similar.
  • Strong software engineering fundamentals with a track record of building reliable, maintainable systems.
  • Proficiency in at least one backend language (we use Python or Rust).
  • Comfort operating across the stack and owning projects end-to-end.
  • Experience in highly collaborative environments involving many different cross-functional partners and subject matter experts.

Preferred qualifications - we encourage you to apply if you meet some but not all of these:

  • Track record building tooling for researchers that achieved high adoption without top down mandates.
  • Experience building or maintaining ML research infrastructure such as training frameworks, evaluation libraries, or experiment tracking systems.
  • Contributions to open-source ML tools or widely-used internal frameworks at research-focused organizations.
  • Record of publications or technical writing on ML systems, infrastructure, or tooling.
  • Background working closely with ML researchers to understand and solve their tooling needs. 
  • Familiarity with distributed systems, modern ML frameworks (PyTorch, JAX), and data processing at scale.
  • Experience with research observability tools, distributed compute frameworks (Ray, Spark), or large-scale evaluation pipelines.
Logistics
  • Location: This role is based in San Francisco, California or New York, NY.
  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
  • Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
  • Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

Apply