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Remote Generative Ai Jobs in California (NOW HIRING)

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 ...

Innowhyte Inc

Develop Generative AI solutions, including chatbots, summarization, and content creation tools. Preprocess, clean, and annotate datasets for training and evaluation. Optimize models for performance ...

TEKsystems

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 ...

New

Twenty80 LLC

AI Engineer

San Mateo, CA · Remote

Flexible remote work environment * Professional development and career growth opportunities * Opportunity to work with cutting-edge generative AI technologies on enterprise-scale deployments

ResourceWell

Field CTO - Bay Area or Remote

San Jose, CA · On-site +1

$200K - $250K/yr

Field CTO - Generative AI About Our Client Our Client is a leader in the development of cutting-edge Artificial Intelligence (AI) solutions, empowering businesses with innovative Generative AI ...

Cypress HCM

Digital Experience Technologist

San Jose, CA · Remote

$85.83 - $114.44/hr

Open to remote candidates. PST Time zone preferred. * Duration: 10/06/2025 to 1/23/2026 * Team ... Investigate and employ new generative AI tools to construct content, workflows, and demos that ...

Adidev Technologies

ML/AI Engineers

Daly City, CA · Remote

Lead cross-functional collaborations to integrate Generative AI models into our offerings ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Adidev Technologies Inc

ML/AI Engineers

Oakland, CA · Remote

... Generative AI. In this role, you will craft and refine AI-driven solutions, turning innovative ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Welo Data

Lead Gen AI Analyst

Santa Clara, CA · On-site +1

We're looking for an experienced Lead Generative AI Analyst to join our team. This leadership role is open to both hybrid and remote candidates, with a preference for those who can work in a hybrid ...

New

Welocalize

Lead Gen AI Analyst

Santa Clara, CA · On-site +1

$50/hr

We're looking for an experienced Lead Generative AI Analyst to join our team. This leadership role is open to both hybrid and remote candidates, with a preference for those who can work in a hybrid ...

New

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All JobsGenerative Ai JobsRemote Generative Ai JobsRemote Generative Ai Jobs in California

Remote Generative Ai information

What is a remote generative AI?

A Remote Generative AI job involves working with artificial intelligence systems that can create new content, such as text, images, or music, from data. These roles are performed remotely, allowing professionals to work from anywhere while developing, training, and deploying generative models like GPT or DALL-E. Job responsibilities may include data preparation, model training, evaluation, and integrating generative AI solutions into products or services. Professionals in this field often collaborate with teams online using cloud-based tools and communication platforms.

What skills and qualifications are needed to thrive as a remote generative AI specialist?

To thrive as a Remote Generative AI Specialist, you need strong expertise in machine learning, deep learning, and programming languages like Python, often supported by a degree in computer science or a related field. Proficiency with frameworks such as TensorFlow or PyTorch, cloud platforms, and relevant certifications (e.g., Google Cloud ML Engineer) is highly beneficial. Effective problem-solving, self-motivation, and clear communication are crucial for collaborating remotely and driving innovative AI solutions. These skills ensure you can develop, deploy, and improve generative AI models efficiently in distributed work environments.

What are common challenges faced by remote generative AI professionals and how can they be addressed?

Remote Generative AI professionals often face challenges such as collaborating effectively across time zones, ensuring data security, and staying updated with rapidly evolving AI technologies. To overcome these, it's important to establish clear communication channels, utilize version control and collaboration tools, and participate in regular team meetings. Additionally, investing time in continuous learning through online courses and AI research communities can help professionals stay current with industry advancements.

What is the difference between Remote Generative Ai vs Data Scientist?

AspectRemote Generative AiData Scientist
Required CredentialsKnowledge of AI/ML, programming skills, familiarity with NLP and deep learningStatistics, programming, data analysis, often a degree in CS, stats, or related fields
Work EnvironmentRemote, collaborative teams, AI research labs, tech companiesRemote or on-site, data analysis teams, research or business units
Industry UsageDeveloping AI models, creating generative content, NLP applicationsAnalyzing data, building predictive models, informing business decisions

Remote Generative Ai specialists focus on creating AI models that generate content, requiring expertise in AI/ML and programming. Data Scientists analyze data to extract insights and build models, often with similar technical backgrounds. While both roles may work remotely and in tech industries, their core functions differ: one develops generative AI systems, the other interprets data for strategic insights.

What are the best remote generative AI jobs?

Remote generative AI jobs include roles such as AI research scientist, machine learning engineer, and data scientist, focusing on developing and deploying AI models like GPT or DALL·E. These positions often require skills in programming, deep learning frameworks, and experience with large language models, with many opportunities available through tech companies, research institutions, and startups. They typically offer flexible schedules and may require certifications or advanced degrees in computer science or related fields.

What jobs can I get with remote generative AI?

Remote generative AI skills can qualify you for roles such as AI content developer, machine learning engineer, data scientist, or AI research scientist. These positions often require knowledge of AI frameworks, programming languages like Python, and experience with large language models or neural networks. Many of these jobs are available in tech companies, research institutions, and startups, often with flexible schedules and remote work options.

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

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

What are popular job titles related to Remote Generative Ai jobs in California?

For Remote Generative Ai jobs in California, the most frequently searched job titles are:

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

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

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

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

Remote Generative Ai jobs near you
Infographic showing various Remote Generative Ai 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.

Senior Generative AI Engineer (Google Gemini & Vertex AI) - Remote

DivIHN

San Diego, CA • On-site, Remote

$110K - $152K/yr

Contractor

Posted 4 days ago

Job description

For further inquiries about this opportunity, please contact one of our Talent Specialists, Justeen at (224)-394-4903
Title: Senior Generative AI Engineer (Google Gemini & Vertex AI) - Remote
Duration: 6 Months with possible for extension
Location: Remote
Candidates must be available to work West Coast (PST) hours.
Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.
Day to Day Responsibilities
  • RAG & Prompt Engineering: Craft and refine effective prompts for RAG, grounding, and context tuning to achieve optimal AI performance in product development.
  • High-Performance API Engineering: Develop asynchronous microservices (FastAPI) using Server-Sent Events (SSE) or WebSockets to stream real-time LLM responses to front-end UIs without backend timeouts.
  • Vector Database Infrastructure: Design, develop, and implement robust Vector Databases using LLMs and modern retrieval technologies to capture information from diverse engineering sources (PDFs, design docs, regulatory guidelines).
  • Data Extraction & Structuring Pipelines: Build and optimize pipelines to extract and structure multi-modal data (tables, text, images) from unstructured documents for LLM training, grounding, and runtime query execution.
  • LLM Fine-Tuning & Training: Fine-tune and train generative AI models using client's engineering data and domain knowledge to create high-accuracy, domain-specific models.
  • GenAI Application & Tool Development: Design and implement scalable backend APIs (FastAPI/REST) and UI integration interfaces so internal engineers can query knowledge bases and analyze data.
  • Automated Requirements Generation: Develop backend functionalities to automatically generate technical requirements from design documents, user stories, and system specification files.
  • Documentation & Knowledge Transfer: Thoroughly document architecture, code, REST endpoints, and model training procedures to enable seamless knowledge transfer to client's internal teams.
  • Cross-Functional Collaboration: Partner closely with Subject Matter Experts (SMEs), System Engineers, and V&V Test teams to optimize AI-powered workflows.
  • AI Guardrails, MLOps & Cost Governance: Implement hallucination checks, PII masking, and guardrails (e.g., NeMo Guardrails) for medical device context. Track token usage, latency, and costs using LangSmith or Vertex AI monitoring.
  • Collaborate closely with engineers and cross-functional teams to design and develop AI solutions.
  • Develop and integrate Generative AI applications and APIs.
  • Work with large datasets, document processing, and data pipelines.
  • Participate in problem-solving, solution design, and technical discussions.
  • Communicate effectively with team members and stakeholders.

Must-Have Qualifications :
  • Relevant Experience & STEM Foundation: 4+ years of professional software/ML engineering experience, with a dedicated AI/ML focus in the last 1-2 years.
  • Google Gemini / Vertex AI (Non-negotiable): Hands-on experience with the Gemini model family and Vertex AI, including deployment, grounding, and integration into production AI services. Hands-on experience with containerization (Docker) and deploying services via Cloud Run or GKE (Kubernetes).
  • Languages & AI Libraries: Proficiency in Python and modern ML/AI frameworks (PyTorch, LangChain, LangSmith) for building autonomous LLM agents, tools, and RAG pipelines.
  • Agent Building & Tool Calling: Proven experience building AI/LLM agents and tool-calling systems in Python against unstructured, multi-source data.
  • Context Engineering & RAG: Expertise in RAG pipelines, prompt engineering, context tuning, grounding, and Vector Databases (e.g., Milvus, Postgres/Pgvector). Clear understanding of advanced RAG architecture including Hybrid Search (Vector + Keyword), Re-ranking models, and semantic caching.
  • Unstructured Data Handling (Non-negotiable): Demonstrated ability to ingest, clean, extract, and structure text, tables, and images from unstructured documents (PDFs, design docs, regulatory files) for LLM training and usage.

Role Information
  • Generative AI Engineer role.
  • Experience in API development.
  • Hands-on experience with Google Gemini and Vertex AI.
  • Knowledge of Agentic AI frameworks and architectures.
  • Strong Python development skills, including experience with LangChain and related AI frameworks.
  • Open to candidates from any industry domain.

Required Skills :
  1. Full Stack Engineering - Building applications for AI-powered services (Backend APIs + Front-End Integration).
  2. Generative AI & LLM Platforms - 2+ years building RAG pipelines & LLM apps using Python, LangChain, and LangSmith.
  3. Agent Building & Unstructured Data - Building AI agents/tool-calling systems in Python and handling unstructured, multi-source data extraction (PDFs, docs).
  4. Strong hands-on experience in Artificial Intelligence and Generative AI
  5. Python programming expertise.
  6. Experience with LangChain and Agentic AI frameworks.
  7. Understanding data handling to pull data from PDFs, design docs, regulatory files

Preferred Skills :
  1. Direct experience architecting and serving custom REST APIs.
  2. Experience in regulated / compliance-sensitive domains (e.g., healthcare / medical device guidelines like FDA, ISO 13485).
  3. Experience integrating multiple LLM APIs beyond a single provider (OpenAI, Bedrock, Claude, or similar).

Additional Preferred Skills
  • Direct experience designing and deploying high-throughput REST APIs (e.g., FastAPI/Flask).
  • Familiarity with medical device development regulations and compliance (e.g., FDA guidelines, ISO 13485).
  • Experience integrating multiple LLM APIs beyond a single vendor (e.g., OpenAI, AWS Bedrock, Anthropic Claude).
  • Front-end development/integration experience for UI design (e.g., Streamlit, Gradio, React/Next.js integration).

Education Requirements:
  • Minimum Bachelors in Software/Computer/IT/Systems/Biomedical Engineering + 3 years

Required Testing:
  • Technical evaluation of Python proficiency, RAG architecture concepts, and API/Agent design.

Software Skills Required:
  • Languages: Python (AsyncIO, OOP), SQL.
  • AI & Agent Frameworks: PyTorch, LangChain, LangSmith, Vertex AI SDK.
  • API & Web Frameworks: FastAPI, Flask, REST APIs, Server-Sent Events (SSE).
  • Databases & Search: Milvus, Pgvector, Qdrant, Redis (caching).
  • Front-End Integration: Streamlit, Gradio, basic React/Next.js.
  • Testing & Guardrails: pytest, JUnit, LangSmith evaluation, NeMo Guardrails.
  • DevOps & Cloud: Docker, GCP (Vertex AI, Cloud Run, GKE), Git.

Required Certifications:
  • Professional certifications specific to AI/ML (e.g., Certified AI Professional / CAIP, Google Cloud ML Engineer) considered a plus.

Interview
  • Number of Interviews: 1,
  • Web Conference (Zoom/ TEAMs)
  • Live problem-solving and technical exercise during the interview.

Apply