ZipRecruiter

Log In

2

Entry Level Generative Ai Engineer Jobs in California

Navisoft

Generative AI Developer

Irvine, CA · On-site

Generative AI Developer (ID: KK11DR11531) Description: This role focuses on developing and implementing solutions using Generative AI technologies. Responsibilities: * Develop and implement ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA · On-site

They are seeking a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. Responsibilities : • ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA · On-site

$200K - $400K/yr

We are looking for a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. This role focuses on ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA

$200K - $400K/yr

We are looking for a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. This role focuses on ...

Kanak Elite Services Inc

AI Engineer

Santa Clara, CA · On-site

We are seeking a Generative AI (GenAI) Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and ...

Innowhyte Inc

We are hiring an AI Engineer specializing in LLMs (Large Language Models), Retrieval Augmented ... Develop Generative AI solutions, including chatbots, summarization, and content creation tools.

Numos AI

Senior AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

We're looking for a Senior AI engineer to build the core intelligence behind AI teammates for ... Experience working with LLMs and generative AI systems * Strong Python skills with frameworks like ...

next page

Showing results 1-20

All JobsGenerative Ai Engineer JobsEntry Level Generative Ai Engineer JobsEntry Level Generative Ai Engineer Jobs in California

Entry Level Generative Ai Engineer information

What is an entry level generative AI engineer?

Entry level generative AI engineers are professionals who work with artificial intelligence technologies focused on creating new content such as images, text, audio, or code. They typically assist in developing, training, and fine-tuning machine learning models like GPT or GANs under the supervision of senior engineers. These roles usually require a strong foundation in programming, mathematics, and machine learning concepts, but may not demand extensive industry experience. Tasks often include data preprocessing, model evaluation, and contributing to research or product development involving generative AI.

What are the key skills and qualifications needed to thrive as an entry level generative AI engineer?

To thrive as an Entry Level Generative AI Engineer, you need a solid background in computer science, mathematics, and machine learning fundamentals, typically supported by a relevant degree or coursework. Familiarity with Python, deep learning frameworks like TensorFlow or PyTorch, and version control systems such as Git is important, along with any foundational certifications in AI or data science. Strong problem-solving ability, curiosity, and effective teamwork skills will help you stand out in this collaborative and innovative field. These skills and qualities are crucial for developing, testing, and improving generative AI models in a rapidly evolving technical landscape.

What are common challenges faced by entry level generative AI engineers, and how can they be addressed?

Entry level Generative AI Engineers often encounter challenges such as mastering complex machine learning frameworks, understanding the nuances of training large models, and keeping up with rapidly evolving research. Collaborating closely with more experienced team members through code reviews and pair programming can accelerate learning. It's also helpful to engage in continuous education through online courses and participate in team discussions to stay updated on the latest advancements and best practices in the field.

What is the difference between Entry Level Generative Ai Engineer vs Data Scientist?

AspectEntry Level Generative Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; basic knowledge of machine learning and programmingBachelor's or higher in CS, Statistics, or related; knowledge of data analysis and modeling
Work EnvironmentTech companies, AI startups, research labs focusing on AI model developmentVarious industries including finance, healthcare, marketing; analyzing data to inform decisions
Employer & Industry UsagePrimarily in AI and tech sectors developing generative modelsAcross multiple sectors using data to solve business problems

While both roles require a background in data and programming, Entry Level Generative Ai Engineers focus on developing AI models like generative adversarial networks, whereas Data Scientists analyze data to generate insights. The former is more specialized in AI model creation, while the latter covers broader data analysis tasks.

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

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

What are popular job titles related to Entry Level Generative Ai Engineer jobs in California?

For Entry Level Generative Ai Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Entry Level Generative Ai Engineer jobs in California look for?

The top searched job categories for Entry Level Generative Ai Engineer jobs in California are:

Entry Level Generative Ai Engineer jobs near you
Infographic showing various Entry Level Generative Ai Engineer job openings in California as of September 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 83% In-person, 4% Hybrid, and 13% Remote job distribution.

Artificial Intelligence (Generative AI) Engineer

San Francisco, CA • On-site

Beehive AI, Inc.
Software Development • 1 - 10 employees
Learn more about Beehive AI, Inc.external

$134K - $162K/yr

Other

Posted 12 days ago

Job description

Artificial Intelligence (Generative AI) Engineer

San Francisco Bay Area (on-site) or USA (remote)

Job Type

Full Time

About the Company

Beehive AI provides a generative AI platform designed specifically for an organization’s unique qualitative data. With self-learning language models, validated by human experts, and built-in statistical analysis, research and insights leaders can quickly, accurately, and safely analyze their qualitative data, and combine it with quantitative data, to generate more robust customer insights.
Beehive AI ingests data from any insights program running in the organization, breaking down silos between data sets and creating a more consistent approach to analysis. Unlike traditional ML/NLP tools that require manual setup and maintenance or new generative AI innovation that rely on generic LLMs and can put your corporate data at risk , Beehive AI uses generative AI and LLMs that are designed specifically for your organization, so you can safely and easily analyze qualitative data at scale, combine it with your quantitative data, and generate robust insights that more accurately reflect your business and your customer at any given point in time.

About the Position

As an Artificial Intelligence (Generative AI) Engineer, you will work on designing, developing, experimenting and maintaining various components of the Beehive AI algorithms and LLMs. You will need to work, often independently, on the full cycle of development starting from researching and experimenting with generative AI solutions all the way to implementing and productionalizing it.

Requirements

Advanced Degree : PhD in Computer Science, AI, Linguistics, Applied Physics or related fields, with a focus on AI and natural language processing.

Experience with LLMs and PyTorch : Extensive experience with large language models and proficiency in PyTorch.

Analytical and Problem-Solving Skills : Ability to address complex challenges in model training and optimization.

Communication and Collaboration Skills : Effective communication skills for conveying technical concepts and collaborating with cross-functional teams.

Innovation and Continuous Learning : Passion for staying updated with the latest trends in AI and machine learning.

#J-18808-Ljbffr

Apply