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Remote Generative Ai Engineer Jobs in Carson, CA

NYFA

Cinematic AI Specialist

Burbank, CA · On-site +1

$55 - $75/hr

Instructors guide students through the practical and creative applications of generative AI tools ... Remote instruction and project-based learning * Collaborative creative environment New York Film ...

Noor Staffing Group

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 ...

SolGenie

AI Lead (SAP Background Required)

Torrance, CA · On-site +1

$106K - $139K/yr

We have got a Remote contract opportunity for AI Lead with one of our clients. The detail of the ... Engineer to design and implement real-world Generative AI solutions across enterprise use cases.

Noor Staffing Group

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 ...

Secret Level

Creative Engineer

Los Angeles, CA · On-site +1

Design and build end-to-end generative workflows using modern AI tools and APIsDevelop new creative capabilities using platforms like ComfyUI, Kling, Google Veo, Seedance, Higgsfield, and Nano Banana

Aprio

Senior AI Product Associate, IT

Los Angeles, CA · On-site +1

$104K - $160K/yr

Work closely with Engineering, tax accountants, and other cross functions to deliver and improve ... Apply generative-AI capabilities relevant to professional services - LLMs, document intelligence ...

Secret Level

Full Stack Engineer

Los Angeles, CA · On-site +1

We're looking for a senior level Full Stack developer for our product engineering team. We are ... Curiosity with Generative AI, creative tools or the entertainment industry. * Experience with real ...

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Remote Generative Ai Engineer information

See Carson, CA salary details

$39.7K

$121.2K

$200.3K

How much do remote generative ai engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote generative ai engineer in Carson, CA is $121,175.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,800.00 and $158,400.00 per year, depending on experience, location, and employer.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

What is the difference between Remote Generative Ai Engineer vs Remote Machine Learning Engineer?

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.

What are popular job titles related to Remote Generative Ai Engineer jobs in Carson, CA?

For Remote Generative Ai Engineer jobs in Carson, CA, the most frequently searched job titles are:

What job categories do people searching Remote Generative Ai Engineer jobs in Carson, CA look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Carson, CA are:

What cities near Carson, CA are hiring for Remote Generative Ai Engineer jobs?

Cities near Carson, CA with the most Remote Generative Ai Engineer job openings:

Remote Generative Ai Engineer jobs near you

Generative AI Senior Developer - Google Cloud (Contract to Hire) - Hybrid Remote - Western States...

Entisys Solutions Inc

Irvine, CA • Remote

$80 - $90/hr

Contractor

Re-posted 5 days ago

Job description

Description

Rate: $80 - $90/ hour (Depending on Experience) 



Note: MUST be US Citizen or Green Card Holder 



***NO RECRUITING AGENCIES***

***NO C2C***

***NO Sponsorship available***




About e360's App Engineering


e360 is a 30+ year privately-owned company with a focus on our people, our clients and leading technologies. e360's Cloud Services Division is a rapidly growing business helping clients manage their Cloud technology. Our team is comprised of leaders that focus on delivering innovative consulting solutions that leverage leading and emerging technologies.  

We are a dynamic and entrepreneurial consulting company that offers ample opportunities for professional development and growth suited to each individual's personal and professional goals. We offer internal, and subsidize external, trainings, and reimburse the cost of technology certification exams and / or renewals. Our family-founded business sees work life fit as a core value that all of our practitioners practice - the value you add to your team is more important than the time that you 'clock in and out.' You will have numerous opportunities to interface with senior leadership, and benefit from mentorship internally or through introductions through external networks to support your growth.  



Description



The Advanced Generative AI Developer is a hands-on consultant responsible for designing, building, and deploying production-ready Generative AI and agentic solutions on Google Cloud.

This role requires strong Python and cloud development experience, practical knowledge of Google Agent Development Kit, Gemini, Vertex AI, and GCP-native application and data services. The consultant will work directly with client and project teams to translate business requirements into secure, scalable, and maintainable AI solutions.



What You'll Do



  • Design, build, test, and deploy Generative AI applications and intelligent agents on Google Cloud.
  • Develop single-agent and multi-agent solutions using Google Agent Development Kit.
  • Integrate Gemini models with enterprise APIs, databases, applications, and business workflows.
  • Deploy AI applications using Agent Engine, Cloud Run, GKE, or other appropriate GCP services.
  • Build Retrieval-Augmented Generation solutions using services such as BigQuery, Vertex AI Vector Search, Cloud Storage, and Document AI.
  • Develop APIs, microservices, agent tools, MCP integrations, and event-driven workflows.
  • Build data pipelines to ingest, transform, chunk, embed, index, and retrieve structured and unstructured data.
  • Implement session management, memory, tool calling, human approval, and agent orchestration patterns.
  • Apply automated testing, CI/CD, logging, monitoring, tracing, evaluation, and cost-management practices.
  • Implement Google Cloud security using IAM, service accounts, Workload Identity Federation, Secret Manager, and private networking.
  • Troubleshoot issues across agents, models, APIs, data pipelines, integrations, security, and cloud deployments.
  • Create architecture diagrams, technical designs, API specifications, deployment guides, and operational documentation.
  • Own technical workstreams and provide design reviews, code reviews, and guidance to other developers.
  • Participate in client discovery, architecture, testing, deployment, and knowledge-transfer activities.

Requirements

  • Significant experience developing and deploying applications on Google Cloud.
  • Advanced Python development experience.
  • Hands-on experience building Generative AI or agentic applications.
  • Experience with Google Agent Development Kit, including agents, tools, workflows, sessions, state, and multi-agent patterns.
  • Experience integrating Gemini models using Vertex AI or Google Gen AI SDKs.
  • Experience with Agent Engine, Cloud Run, GKE, Cloud Functions, or similar GCP runtimes.
  • Experience designing and implementing RAG solutions.
  • Experience with BigQuery and Google Cloud data services.
  • Experience building APIs using frameworks such as FastAPI.
  • Experience with REST APIs, asynchronous processing, event-driven architecture, and microservices.
  • Understanding of MCP and its use in connecting agents to enterprise tools and systems.
  • Experience with SQL, document stores, object storage, embeddings, semantic search, or vector databases.
  • Experience with Git, automated testing, CI/CD, Docker, and infrastructure as code.
  • Understanding of Google Cloud IAM, service accounts, Secret Manager, networking, logging, and monitoring.
  • Ability to evaluate tradeoffs involving model quality, latency, security, scalability, reliability, and cost.

Candidates are not expected to have experience with every listed GCP service. However, they must have hands-on experience delivering Generative AI solutions and be able to explain their architecture and implementation decisions.




Preferred Qualifications



  • Experience delivering client-facing Google Cloud consulting projects.
  • Experience leading a technical workstream from discovery through production deployment.
  • Experience deploying ADK agents using Agent Engine, Cloud Run, or GKE.
  • Experience implementing MCP servers, custom agent tools, or enterprise integrations.
  • Experience with Vertex AI Vector Search, BigQuery Vector Search, Document AI, Apigee, Pub/Sub, Eventarc, or Workflows.
  • Experience with Terraform, Cloud Build, Artifact Registry, and automated GCP deployment pipelines.
  • Experience implementing AI evaluation, agent testing, observability, guardrails, and cost monitoring.
  • Relevant Google Cloud certifications.



Professional Skills



  • Strong consulting, communication, and problem-solving skills.
  • Ability to translate business requirements into practical technical solutions.
  • Ability to explain complex AI and cloud concepts to technical and non-technical stakeholders.
  • Strong documentation and technical leadership skills.
  • Ability to work independently and manage changing project priorities.
  • Ability to identify and communicate technical risks, dependencies, and blockers.
  • Willingness to mentor other developers and contribute to reusable delivery standards.



Critical Success Factors



  • Ability to independently design and deliver production-ready AI solutions on Google Cloud.
  • Strong practical knowledge of Google ADK, Gemini, Vertex AI, and GCP architecture.
  • Ability to build agents that securely interact with APIs, data, tools, and enterprise systems.
  • Ability to determine when to use agentic, deterministic, serverless, containerized, or managed-service patterns.
  • Commitment to security, testing, observability, governance, maintainability, and cost control.
  • Ability to own technical workstreams and consistently deliver high-quality client outcomes.

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