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Research Programmer Jobs in California (NOW HIRING)

OpenAI

Research Engineer

San Francisco, CA · On-site

$250K - $445K/yr

About the Role As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking ...

Nace AI

Research Engineer

Palo Alto, CA · On-site

... research and engineering teams. Qualifications : Required : • Direct experience working with Large Language Models (LLMs) or Vision-Language Models (VLMs) in research or production settings. • ...

Waabi

Research Engineer

San Francisco, CA · On-site +1

$122K - $215K/yr

To learn more visit: www.waabi.ai As a Research Engineer, you will be at the forefront of advancing and deploying artificial intelligence algorithms for our self-driving vehicles. You will work ...

Meta

AI Research Engineer

Menlo Park, CA

We're hiring Research Engineers to join teams across Meta working at the intersection of frontier AI and real-world product impact. You'll be embedded d.

Waabi

Research Engineer

San Francisco, CA · On-site +1

$122K - $215K/yr

  • Medical

  • Dental

  • Vision

  • PTO

To learn more visit: www.waabi.ai As a Research Engineer, you will be at the forefront of advancing and deploying artificial intelligence algorithms for our self-driving vehicles. You will work ...

Applied Compute

Platform Research Engineer

San Francisco, CA · On-site

$200K - $335K/yr

  • Medical

  • Retirement

  • PTO

The role As a platform research engineer, you'll do research around ways to make Applied Compute's platform intelligent. This includes how we set up continual learning against production traces (OPSD ...

DepthFirst

Research Engineer

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

About this role We're seeking an experienced Research Engineer to join our effort in building and training AI agents for vulnerability discovery and exploitation. We are building a technology capable ...

Real-Time Innovations

Research Engineer

Sunnyvale, CA · On-site +1

  • PTO

To help drive this mission, we are looking for a Research Engineer to tackle the industry's toughest challenges, including enabling AI coding for distributed systems, delivering determinism and ...

Console Systems, Inc

Research Engineer

San Francisco, CA · On-site

$200K - $350K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

About the role We're hiring a Research Engineer to push Console's core agent loop from powerful to truly self-improving. As more customers rely on Console to automate critical back-office operations ...

Real-Time Innovations

Research Engineer

Sunnyvale, CA · On-site

  • PTO

To help drive this mission, we are looking for a Research Engineer to tackle the industry's toughest challenges, including enabling AI coding for distributed systems, delivering determinism and ...

Harvey

Research Engineer, Post-Training

San Francisco, CA · On-site

$231K - $340K/yr

We are looking for a research engineer who can help scale that loop: defining and running model training experiments, interpreting results, and working with internal and external research partners to ...

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All JobsResearch Programmer JobsResearch Programmer Jobs in California

Research Programmer information

See California salary details

$10.9K

$111.3K

$127.3K

How much do research programmer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for research programmer in California is $111,322.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,700.00 and $127,300.00 per year, depending on experience, location, and employer.

What is a research programmer?

Research programmers are professionals who develop software, algorithms, and computational tools to support academic or scientific research projects. They work closely with researchers to design, implement, and optimize code for data analysis, simulations, and experiments. Their role often involves adapting existing software or creating new applications to solve specific research problems, ensuring that the software meets the requirements of the research team. Research programmers may also contribute to writing technical documentation and publishing results.

What is the difference between Research Programmer vs Data Analyst?

AspectResearch ProgrammerData Analyst
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; programming skillsBachelor's or Master's in Statistics, Data Science, or related fields; analytical skills
Work EnvironmentResearch labs, academic institutions, tech companiesBusiness, healthcare, finance, or marketing sectors
Employer & Industry UsageResearch projects, academic research, R&D departmentsData interpretation, reporting, and decision support in organizations

Research Programmers focus on developing software and tools for research purposes, often working in academic or research settings. Data Analysts interpret data to provide insights for business decisions. While both roles require strong technical skills, Research Programmers emphasize programming and software development, whereas Data Analysts focus on data interpretation and visualization.

How do research programmers typically collaborate with researchers and other team members during a project?

Research Programmers often work closely with principal investigators, data scientists, and subject matter experts to develop, test, and optimize software solutions tailored to research needs. Collaboration is highly iterative and may involve regular meetings to align on project goals, troubleshoot technical challenges, and adapt code to evolving research requirements. Effective communication and a flexible approach are key, as programmers frequently translate complex research concepts into functional code and may also assist with data analysis or visualization tasks.

What are the key skills and qualifications needed to thrive as a research programmer, and why are they important?

To thrive as a Research Programmer, you need a strong background in computer science, programming languages (such as Python, Java, or C++), and a relevant bachelor's or master's degree. Familiarity with scientific computing tools, version control systems (like Git), and data analysis platforms is typically required. Analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with research teams and translate complex requirements into code. These skills enable you to develop robust software solutions that advance research goals and ensure project success.

What are popular job titles related to Research Programmer jobs in California?

For Research Programmer jobs in California, the most frequently searched job titles are:

What job categories do people searching Research Programmer jobs in California look for?

The top searched job categories for Research Programmer jobs in California are:

What cities in California are hiring for Research Programmer jobs?

Cities in California with the most Research Programmer job openings:

What are popular job titles related to Research Programmer jobs in CA?

For Research Programmer jobs in CA, the most frequently searched job titles are:

Research Programmer jobs near you
Infographic showing various Research Programmer job openings in California as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 10% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $111,322 per year, or $53.5 per hour.

Applied Research Engineer

Hirekeyz Inc

San Francisco, CA • On-site

Full-time

Re-posted 4 days ago

Job description

Position: Applied Research Engineer

Location - San Francisco, CA - Hybrid

Job Type: Full Time

Job Description:

Role Overview

As an Applied Research Engineer at Labelbox, you’ll play a critical role in shaping the future of human-in-the-loop AI systems. You’ll design and implement advanced methods to align human feedback with the training of cutting-edge AI models, including techniques like Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), and other alignment strategies. You’ll also develop innovative tools to measure and enhance the quality of human-generated data and build AI-assisted systems that streamline and improve the data labeling process.

Your work will directly influence the performance and reliability of frontier models by ensuring they reflect human preferences more accurately. By bridging research with real-world applications, you’ll help bring scalable, impactful alignment solutions into production for some of the world’s most advanced AI developers.

Your Impact
  • Drive advances in AI alignment, developing state-of-the-art techniques like RLHF and new methods to ensure models align with human intent.
  • Improve human-in-the-loop data quality by building robust systems for measurement, feedback analysis, and refinement.
  • Create AI-assisted labeling tools using active learning, adaptive sampling, and automation to enhance speed and accuracy.
  • Investigate the role of different feedback types—like preferences, critiques, and demonstrations—on model training and alignment.
  • Develop algorithms to improve how AI systems learn from human input, increasing adaptability and response quality.
  • Integrate alignment innovations into the Labelbox product suite, making human feedback workflows scalable for customers.
  • Collaborate with customers and the AI research community to shape best practices for training large-scale models.
  • Contribute to the field through publications, conference presentations, and open research.
  • Stay ahead of the curve by exploring emerging trends in AI alignment, data quality, and human-AI collaboration.
  • Help establish Labelbox as a thought leader in human-centric AI by producing high-quality technical and educational content.
What You Bring
  • Advanced degree (Ph.D. or Master’s) in Computer Science, Machine Learning, AI, or a related field.
  • 3+ years of experience solving complex ML challenges and building production-ready AI systems.
  • Proven track record in data quality systems, with a strong understanding of how they affect model performance.
  • Deep knowledge of frontier models, including large language models and multimodal systems, and how to optimize them using human feedback.
  • Strong programming skills in Python, with hands-on experience in PyTorch, JAX, or TensorFlow.
  • Contributions to the research community through peer-reviewed publications in top AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL).
  • Ability to translate research into real-world solutions, from prototype to scalable deployment.
  • Strong analytical thinking and a structured approach to solving open-ended AI problems.
  • Excellent collaboration and communication skills to work effectively across technical teams and with external stakeholders.