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Training Ai Models Jobs in California (NOW HIRING)

NVIDIA

Solutions Architect, AI Models

Santa Clara, CA · On-site

$74 - $97.50/hr

... training, post-training, reinforcement learning (RL), evaluation, and model optimization. • ... AI solutions. • As we work with customers across multiple industries, we help improve NVIDIA ...

Nvidia

Solutions Architect, AI Models

Santa Clara, CA

$74 - $97.50/hr

Tackle sophisticated AI challenges by applying skills across the AI model lifecycle-from data processing and orchestration to training, post-training, reinforcement learning (RL), evaluation, and ...

Cerebras Systems

$148K - $196K/yr

This architecture allows Cerebras to deliver industry-leading training and inference speeds; over ... As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our ...

Cerebras

Senior Product Manager, AI Models

Sunnyvale, CA · On-site

$150 - $220/hr

This architecture allows Cerebras to deliver industry-leading training and inference speeds; over ... As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our ...

Adam

Founding Research Engineer

San Francisco, CA · On-site

Adam is building the founding research team to tackle the challenge of training AI models for interpreting and editing parametric CAD in 3D space. The role involves training models, optimizing ...

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Training Ai Models information

What is a training AI model?

A Training AI Models job involves developing, refining, and optimizing machine learning models by providing them with relevant data, adjusting parameters, and evaluating their performance. Professionals in this role clean and preprocess data, select appropriate algorithms, and fine-tune models for accuracy and efficiency. They may also work with engineers and researchers to ensure models generalize well to real-world applications. The goal is to create AI systems that perform specific tasks effectively, such as natural language processing, image recognition, or predictive analytics.

What are common challenges faced when training AI models, and how are they addressed?

One of the most common challenges in training AI models is handling large, complex datasets that often contain errors or inconsistencies, which can impact model performance. Professionals in this role frequently collaborate with data engineers and subject matter experts to clean and properly label data, as well as implement quality assurance checks throughout the process. Additionally, tuning model parameters and addressing issues such as overfitting or underfitting often require experimentation and iterative testing. Most teams employ version control and hold regular review sessions to ensure best practices are followed, making collaboration and communication essential parts of overcoming these challenges.

What are the key skills and qualifications needed to thrive in the training AI models position, and why are they important?

To thrive in Training AI Models, you need strong programming skills in languages like Python, a solid understanding of machine learning concepts, and typically a degree in computer science, data science, or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and familiarity with data preprocessing and annotation tools are commonly required; certifications in AI or data science can be advantageous. Effective communication, keen attention to detail, and collaboration are vital soft skills for working with cross-functional teams and ensuring data quality. These abilities are crucial for developing accurate models, delivering impactful AI solutions, and maintaining high standards throughout the model development lifecycle.

Can you get paid to train AI models?

Training AI models is a job that can be paid, especially for roles such as AI trainers, data annotators, or machine learning engineers. Compensation varies based on experience, location, and the complexity of the tasks, and often involves working with labeled datasets, coding, and understanding AI frameworks.

How to become a training AI models?

To become a training AI models professional, develop strong skills in programming languages like Python, understand machine learning algorithms, and gain experience with data preprocessing and model evaluation. Familiarity with frameworks such as TensorFlow or PyTorch and a background in computer science or data science are also important. Certifications or courses in AI and machine learning can enhance your qualifications.

What job trains AI models?

A job that trains AI models is typically called an AI/ML engineer or data scientist. These roles involve developing, testing, and refining machine learning algorithms using programming skills in languages like Python and tools such as TensorFlow or PyTorch. They often require knowledge of data preprocessing, model evaluation, and experience with large datasets.

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

The most popular types of Training Ai Models jobs in California are:

What are popular job titles related to Training Ai Models jobs in California?

For Training Ai Models jobs in California, the most frequently searched job titles are:

What job categories do people searching Training Ai Models jobs in California look for?

The top searched job categories for Training Ai Models jobs in California are:

What cities in California are hiring for Training Ai Models jobs?

Cities in California with the most Training Ai Models job openings:

Training Ai Models jobs near you
Infographic showing various Training Ai Models job openings in California as of August 2026, with employment types broken down into 60% Full Time, 22% Part Time, and 18% Contract. Highlights an 58% In-person, and 42% Remote job distribution.

Drone Pilot for AI Training and Data Collection

TSMG

San Francisco, CA

Full-time

Re-posted 21 days ago

Job description

We are seeking an experienced and highly skilled Drone Pilot to assist in the development and training of AI models, specifically in the areas of computer vision, sensor fusion, and autonomous navigation. The ideal candidate will be responsible for collecting high-quality data in real-world environments, contributing to the optimization of AI algorithms that power autonomous systems.

As a Drone Pilot for AI & Autonomous Systems Training, you will operate advanced drones to capture data essential for training and validating AI models that power autonomous navigation, object detection, and decision-making systems.
Key Responsibilities:
  • Pilot drones equipped with high-resolution cameras, LiDAR, thermal imaging, and other sensors to collect diverse datasets used for training AI algorithms, particularly for autonomous navigation, computer vision, and sensor fusion.
  • Capture data in various real-world conditions (e.g., urban, rural, industrial, challenging weather conditions) to expose AI systems to a wide range of environments and scenarios.
  • Execute complex drone missions with precise data collection objectives, such as aerial mapping, 3D reconstruction, obstacle detection, and object tracking.
  • Collaborate closely with AI engineers, machine learning specialists, and autonomous systems teams to ensure data collection aligns with the specific requirements of AI model training.
  • Perform post-flight data quality checks and initial preprocessing to ensure the datasets are ready for use in training AI models.
  • Operate drones in both manual and autonomous modes, supporting AI-driven flight operations where drones rely on onboard algorithms for navigation and decision-making.
  • Adhere to Federal Aviation Administration (FAA) and local aviation regulations governing drone operations, ensuring the safe and compliant conduct of all drone missions.
  • Oversee the maintenance, calibration, and troubleshooting of drones and onboard sensors to ensure the highest standards of performance and reliability.
Qualifications:
  • Commercial drone pilot certification (FAA Part 107 or equivalent), with additional certifications in safety or advanced drone technologies considered a plus.
  • Proven track record as a drone pilot, with significant experience in collecting data for industrial, research, or AI-focused applications.
  • Expertise in flying drones equipped with advanced sensors such as LiDAR, thermal cameras, RGB cameras, and multispectral sensors.
  • Familiarity with the nuances of autonomous flight, sensor integration, and machine learning workflows, especially those that involve real-time data processing.
  • Strong understanding of how drone-collected data is used for AI training, including its role in training AI for perception, navigation, and decision-making.
  • Experience in using software for flight planning, such as Pix4D, DroneDeploy, or similar platforms, and geospatial data analysis tools.
  • Familiarity with machine learning concepts, especially those related to computer vision (e.g., image segmentation, object detection, and tracking) and autonomous navigation systems.
  • Basic understanding of geospatial data processing, photogrammetry, and 3D reconstruction techniques for AI applications.
  • Strong attention to detail with a commitment to ensuring the highest quality of data collection and analysis.
  • Excellent communication and collaboration skills, with the ability to work in multidisciplinary teams.
We would be happy to get to know you and your skills better and see how we can support each other's growth.

Please apply and let's meet!
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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