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Ai Lab Jobs in California (NOW HIRING)

Kastle

Staff AI Engineer

San Francisco, CA · On-site

Kastle is building an AI operating system for consumer lending, focusing on mortgage solutions. The role involves fine-tuning large language models and designing AI workflows for compliance in ...

Cogent Security

Cogent AI Fellowship

San Francisco, CA · On-site

$100K - $300K/yr

About Cogent Cogent is an Applied AI Lab building the next generation of AI agents for cybersecurity. AI has fundamentally changed how attacks happen, allowing malicious actors to operate at ...

Nexxa.ai

Senior AI Architect

San Francisco, CA · On-site

This role is ideal for candidates with experience at a frontier AI company, top research lab, or PhD‑level background who want their work to directly shape product and user experience rather than ...

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Ai Lab information

What is an AI Lab?

An AI Lab is a specialized research and development center focused on artificial intelligence technologies. These labs typically bring together scientists, engineers, and researchers to work on advancing machine learning, data science, robotics, and related fields. AI Labs can be part of universities, tech companies, or independent organizations, and they often collaborate on cutting-edge projects, publish research, and develop AI-powered solutions for real-world problems. Their work plays a crucial role in shaping how AI is integrated into various industries and society.

What are the key skills and qualifications needed to thrive in an AI Lab, and why are they important?

To thrive in an AI Lab, you need strong expertise in machine learning, statistics, and programming, often supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and cloud computing platforms, as well as experience with data management systems, is typically required. Creative problem-solving, collaboration, and excellent communication skills help distinguish top contributors in this environment. These skills ensure effective research, innovation, and teamwork, driving successful AI development and implementation.

What are some common challenges faced when working in an AI Lab, and how can new team members overcome them?

Working in an AI Lab often involves tackling rapidly evolving technologies and collaborating with experts from diverse backgrounds, such as data scientists, engineers, and domain specialists. New team members may find it challenging to stay updated on cutting-edge research and to bridge communication gaps between different disciplines. To overcome these challenges, it's helpful to regularly attend team meetings, engage in knowledge-sharing sessions, and seek mentorship from experienced colleagues. Emphasizing continuous learning and open communication greatly enhances both individual growth and team success.

What is the difference between Ai Lab vs Data Scientist?

AspectAi LabData Scientist
Required CredentialsTypically a degree in computer science, AI, or related fields; certifications in AI/ML are commonDegree in statistics, computer science, or related fields; certifications in data analysis or machine learning are common
Work EnvironmentResearch labs, tech companies, or R&D departments focusing on AI developmentBusiness environments, analyzing data to inform decisions, often in tech, finance, or healthcare
Employer & Industry UsagePrimarily in tech companies, research institutions, and AI startupsAcross industries like finance, healthcare, marketing, and tech firms

While both roles involve working with data and algorithms, an Ai Lab focuses on developing and researching AI technologies, whereas a Data Scientist analyzes data to generate insights and support decision-making. The roles often overlap but differ mainly in their primary objectives and work environments.

How do I get into an AI lab?

To join an AI lab, candidates typically need a strong background in computer science, machine learning, or related fields, often demonstrated through a relevant degree or research experience. Gaining skills in programming languages like Python, familiarity with AI frameworks such as TensorFlow or PyTorch, and participating in research projects or internships can improve chances. Networking with professionals and publishing work can also help in securing a position in an AI lab.

What is the easiest AI Lab job to get into?

Entry-level roles in AI labs such as data annotation, data labeling, or research assistant positions are generally the easiest to obtain. These jobs often require basic technical skills, familiarity with AI concepts, and sometimes a relevant degree or certification, making them accessible for newcomers to the field.

What job categories do people searching Ai Lab jobs in California look for?

The top searched job categories for Ai Lab jobs in California are:

What cities in California are hiring for Ai Lab jobs?

Cities in California with the most Ai Lab job openings:

Ai Lab jobs near you
Infographic showing various Ai Lab job openings in California as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Visiting Scholar -- Post Training & Research (Discovery AI Lab)

Meta

Menlo Park, CA • On-site, Remote

$219K - $301K/yr

Full-time

Posted 9 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 246 rated software companies

Job description

Discovery AI Lab is pioneering large language model (LLM) technologies across the full ML lifecycle — pre-training, mid-training, and post-training — to replace traditional recommendation pipelines with generative AI. Our work spans preference alignment and reinforcement learning for recommendation systems, self-improving agentic AI, and efficient training and inference at scale. We publish at top venues (NeurIPS, ICML, ICLR, RecSys) while shipping research directly into products that serve billions of users.We are seeking a Visiting Scholar to join the team for a 12-month, full-time research engagement. This role offers the opportunity to lead cutting-edge research embedded within a world-class team, with access to Meta-scale infrastructure, data, and compute.
Visiting Scholar — Post Training & Research (Discovery AI Lab) Responsibilities:
  • Lead research on post-training algorithms for generative recommendation systems, including preference alignment methods (e.g., DPO, GRPO, SimPO) adapted for multi-objective recommendation signals.
  • Design and develop self-improving agent frameworks that leverage multi-agent collaboration, LLM self-correction, and continuous-learning loops.
  • Advance efficient inference techniques — including quantization, compression, and distillation — for large-scale generative and Mixture-of-Experts recommendation models.
  • Collaborate with research scientists and engineers to translate research into production-ready systems at Meta scale.
  • Mentor research scientists and engineers on the team, upleveling internal capabilities in post-training and agentic AI.

Minimum Qualifications:
  • PhD in Computer Science, Machine Learning, Natural Language Processing, or a related field
  • Active faculty appointment or equivalent research position at a university or research institution
  • Demonstrated publication record at top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, RecSys)
  • Expertise in one or more of: post-training methods (RLHF, preference optimization, reward modeling), large language models, or agentic AI systems
  • Experience conducting research in collaborative, team-based environments
  • Available for a full-time, 12-month on-site or hybrid engagement
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Preferred Qualifications:
  • Tenured or tenure-track faculty position
  • Research focus at the intersection of LLMs and recommendation systems
  • Experience with reinforcement learning for language models or multi-agent systems
  • Published work on model compression, quantization, or efficient inference for large-scale models
  • Prior industry research experience (internship or collaboration) with production ML systems
  • Track record of mentoring graduate students or junior researchers

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$219,000/year to $301,000/year + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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