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Remote Ai Engineer Jobs in California (NOW HIRING)

... AI Engineers (Enterprise) to help design, build, and deploy production-grade generative AI ... Remote-friendly within the United States * Preference for candidates located near major East or ...

AI Engineer

San Diego, CA · Remote

$50 - $58/hr

Remote AI/ML Software Engineer, Generative AI Are you passionate about building Generative AI systems that move beyond prototypes and create real business impact? A leading healthcare technology ...

Posted today

AI Engineer

San Francisco, CA · Remote

$150K - $210K/yr

AI Engineer - Agentic Automation Location ... Remote Compensation: $150,000 - $210,000 Join a rapidly growing company disrupting the trucking ...

AI Engineer

San Francisco, CA · On-site +1

$155K - $180K/yr

We are looking for an AI Engineer to help build our next-generation conversational AI experiences ... We will also consider highly qualified remote candidates who can travel to San Francisco for in ...

While we are a remote-first company, the nature of this role requires candidates to be based in the ... ML/AI Engineering: Experience building MLOps pipelines and/or developing, deploying, and iterating ...

Lead AI Engineer

Los Angeles, CA · Remote

$160K - $180K/yr

Lead AI Engineer, Mortgage Automation About the Company We're a fast growing mortgage lender using ... Location: Remote * Full time, exempt Responsibilities * Lead end to end design, delivery, and ...

Lead AI Engineer

Los Angeles, CA · Remote

$160K - $180K/yr

Lead AI Engineer, Mortgage Automation About the Company We're a fast growing mortgage lender using ... Location: Remote * Full time, exempt Responsibilities * Lead end to end design, delivery, and ...

We are hiring an AI Engineer specializing in LLMs (Large Language Models), Retrieval Augmented Generation ( RAG ), and Generative AI. The role involves building advanced AI solutions that leverage ...

Software AI Engineer2 Experience: 6 - 8 yrs Location: 1 - US Bay Area 1 - US Remote Key ... Collaborate with data scientists and other engineers to integrate AI models into existing systems.

Sr. AI Engineer

San Francisco, CA · On-site +1

$65 - $83.75/hr

Employee divides their time between in-office and remote work. Access to an office location is ... engineering experience * 3+ years in AI/ML engineering, LLM-based systems, or advanced SaaS ...

Explainable AI Engineer

Palo Alto, CA · Remote

$122K - $165K/yr

We're hiring an Explainable AI Engineer to build, verify, and validate business impact predictions ... This is a remote position. USA, Nationwide. * You will have an opportunity to start as a contractor ...

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Remote Ai Engineer information

See California salary details

$25

$52

$75

How much do remote ai engineer jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for remote ai engineer in California is $52.93, according to ZipRecruiter salary data. Most workers in this role earn between $42.69 and $61.44 per hour, depending on experience, location, and employer.

What is a remote AI engineer?

A Remote AI Engineer is a professional who designs, develops, and deploys artificial intelligence models and systems while working from a remote location. They use machine learning, deep learning, and data science techniques to build AI-powered applications, improve automation, and solve complex problems. Responsibilities often include data preprocessing, model training, fine-tuning, and integrating AI solutions into products or services. These engineers collaborate with cross-functional teams online, using cloud-based tools and platforms for development and deployment. Remote AI Engineers typically need strong programming skills in languages like Python, experience with frameworks like TensorFlow or PyTorch, and familiarity with cloud computing and MLOps.

What is it like collaborating with team members as a remote AI engineer?

As a Remote AI Engineer, collaboration typically occurs through virtual meetings, code reviews, shared documentation, and messaging platforms like Slack or Teams. You will work closely with data scientists, product managers, and software engineers to define requirements, design solutions, and integrate AI models into products or services. Strong communication and proactive reporting are highly valued to ensure project alignment and seamless progress. Effective collaboration in a remote setting not only enhances project outcomes but also fosters professional growth and a sense of team cohesion.

What are the most commonly searched types of Ai Engineer jobs in California?

The most popular types of Ai Engineer jobs in California are:

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

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

What cities in California are hiring for Remote Ai Engineer jobs?

Cities in California with the most Remote Ai Engineer job openings:

Infographic showing various Remote Ai Engineer 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, with an average salary of $110,091 per year, or $52.9 per hour.

AI Engineer

Twenty80 LLC

San Mateo, CA • Remote

Full-time

Medical, Dental, Vision

Posted 21 days ago


Job description

Role Summary

Our client, a rapidly growing AI infrastructure company, is seeking multiple AI Engineers (Enterprise) to help design, build, and deploy production-grade generative AI solutions for enterprise customers.

This is a customer-facing, hands-on engineering role that combines deep technical expertise with solution architecture and client engagement. You will partner closely with enterprise organizations to transform generative AI concepts into scalable production systems while collaborating with internal engineering and product teams to drive innovation.

Strong candidates will have experience deploying AI/ML solutions in production environments, working with large language models (LLMs), and supporting enterprise customers through complex technical implementations.


Key ResponsibilitiesEnterprise AI Solutions
  • Lead technical discovery sessions with enterprise customers to understand business requirements and define AI solution strategies.
  • Scope and execute proof-of-concept (POC) projects, performance testing, and solution evaluations.
  • Design, build, and deploy production-ready AI applications within customer environments.
  • Recommend appropriate model architectures, deployment strategies, and infrastructure based on customer requirements.
  • Advise customers on model fine-tuning and optimization techniques, including supervised fine-tuning and other modern training approaches.
  • Develop evaluation frameworks to measure model performance and production readiness.
Customer Engagement
  • Serve as the primary technical advisor for enterprise customers throughout implementation and deployment.
  • Build relationships with technical and executive stakeholders.
  • Guide customers through infrastructure, security, and compliance considerations.
  • Support successful production rollouts and ongoing technical adoption.
Cross-Functional Collaboration
  • Partner with Product and Engineering teams to communicate customer feedback and influence product improvements.
  • Identify recurring customer challenges and contribute to product roadmap discussions.
  • Collaborate internally to improve deployment processes and customer success.

Required Qualifications
  • 3+ years of experience in customer-facing AI/ML, machine learning infrastructure, solutions engineering, or related technical roles
  • Proven experience deploying AI/ML applications into production environments
  • Hands-on experience with large language model (LLM) inference and/or model training using open-source model frameworks
  • Strong Python programming skills
  • Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
  • Experience with containerization and orchestration technologies, including Kubernetes
  • Excellent communication skills with the ability to engage both technical teams and executive stakeholders
  • Ability to manage multiple enterprise projects in a fast-paced environment

Preferred Qualifications
  • Experience with modern LLM fine-tuning methodologies such as supervised fine-tuning (SFT) and other advanced optimization techniques
  • Background in enterprise AI solution architecture or technical consulting
  • Experience working within high-growth startup environments
  • Strong understanding of enterprise infrastructure, security, and compliance requirements
  • Experience supporting large-scale customer deployments

Ideal Candidate Profile

Successful candidates typically have:

  • Experience building and deploying production AI solutions rather than purely research or advisory work
  • Strong knowledge of open-source LLM frameworks and inference platforms
  • Experience working directly with enterprise customers throughout implementation and deployment
  • The ability to translate complex technical concepts for both engineering teams and executive leadership
  • A collaborative mindset with a passion for solving complex customer challenges
  • Experience working in fast-paced, high-growth environments

Schedule & Travel
  • Full-time position
  • Remote-friendly within the United States
  • Preference for candidates located near major East or West Coast metropolitan areas, though exceptional remote candidates will be considered
  • Regular domestic travel to customer sites for technical discovery, proof-of-concept implementations, and production deployments

Compensation
  • Competitive base salary
  • Performance-based bonus or on-target earnings (OTE)
  • Equity package
  • Compensation commensurate with experience and qualifications

Benefits
  • Comprehensive medical, dental, and vision insurance
  • Equity participation
  • Performance-based bonus opportunities
  • Flexible remote work environment
  • Professional development and career growth opportunities
  • Opportunity to work with cutting-edge generative AI technologies on enterprise-scale deployments
  • Collaborative, fast-paced engineering culture