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Entry Level Generative Ai Engineer Jobs in California

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.

Aivra Health LLC

AI/ML Engineer

California City, CA · On-site

Experience with Generative AI or LLMs is a plus. * Knowledge of MLOps tools is preferred. * Strong analytical and problem-solving skills. Keywords AI Engineer, Machine Learning Engineer, Deep ...

New

Expleo

AI Engineer

Los Angeles, CA

Nous recherchons un(e) AI Engineer passionné(e) par les technologies d'Intelligence Artificielle ... Concevoir et développer des solutions basées sur les technologies Generative AI : * RAG ...

Expleo

AI Engineer

Los Angeles, CA · On-site

Missions Nous recherchons un(e) AI Engineer passionne(e) par les technologies d'Intelligence ... Concevoir et developper des solutions basees sur les technologies Generative AI : * RAG (Retrieval ...

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 ...

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Entry Level Generative Ai Engineer information

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 entry level generative AI engineers?

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, and why are they important?

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 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:
What cities in California are hiring for Entry Level Generative Ai Engineer jobs? Cities in California with the most Entry Level Generative Ai Engineer job openings:
Entry Level Generative Ai Engineer jobs near you
Helix AI Engineer, Generative AI

Helix AI Engineer, Generative AI

Figure

San Jose, CA • On-site

$200K - $400K/yr

Full-time

Re-posted 11 days ago

Job description

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is to build embodied AI systems that can perceive, reason, and act in the real world. Figure is headquartered in San Jose, CA, and this role requires 5 days/week in-office collaboration.
Our Helix team is responsible for developing the core AI systems that power humanoid autonomy. 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 training and deploying diffusion and generative models across vision, video, and multimodal domains, with applications spanning perception, data generation, and model-based reasoning.
Responsibilities
  • Design, train, and deploy large-scale generative models, with a focus on diffusion-based approaches for vision, video, and multimodal data
  • Develop models that improve robot perception, world modeling, and prediction from raw sensory inputs
  • Build generative systems for synthetic data creation, augmentation, and dataset scaling for robot learning
  • Explore and implement state-of-the-art techniques in diffusion, generative modeling, and multimodal foundation models
  • Optimize training pipelines for large-scale generative models across distributed systems
  • Work closely with data, training infrastructure, and agent teams to integrate generative models into the full autonomy stack
  • Evaluate model quality, robustness, and generalization across real-world scenarios
  • Contribute to the design of scalable experimentation frameworks for generative model development
Requirements
  • Experience training and deploying generative models (diffusion, autoregressive, or related approaches) at scale
  • Strong understanding of modern deep learning techniques for vision and/or multimodal systems
  • Proficiency in Python and deep learning frameworks such as PyTorch
  • Experience working with large-scale datasets and distributed training systems
  • Strong experimental rigor and ability to iterate quickly on model performance
  • Solid software engineering skills and ability to build reliable, maintainable systems
  • Ability to operate independently and own ambiguous, high-impact technical problems
Bonus Qualifications
  • Experience with diffusion models for image or video generation
  • Experience with multimodal foundation models (vision-language or vision-language-action)
  • Background in synthetic data generation or simulation for robotics or embodied AI
  • Experience optimizing large-scale training (multi-node, GPU clusters, etc.)
  • Familiarity with 3D, video prediction, or world models
  • Prior work in robotics, embodied AI, or real-world ML systems
  • Publication record in machine learning, computer vision, or generative modeling

The US base salary range for this full-time position is between $200,000 - $400,000
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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