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Software Engineer Ai Model Training Jobs in California

Vast

Staff Software Engineer, AI Tooling

Long Beach, CA · On-site

$188K - $267K/yr

Build and maintain production-grade integrations connecting AI models with internal tools, data ... Senior Software Engineer, AI Tooling: $159,900 - $226,900 * Staff Software Engineer, AI Tooling ...

Vast

Staff Software Engineer, AI Tooling

Long Beach, CA

$188K - $267K/yr

Build and maintain production-grade integrations connecting AI models with internal tools, data ... Senior Software Engineer, AI Tooling: $159,900 - $226,900 * Staff Software Engineer, AI Tooling ...

Vast

Staff Software Engineer, AI Tooling

Long Beach, CA · On-site

$188K - $267K/yr

Build and maintain production-grade integrations connecting AI models with internal tools, data ... Senior Software Engineer, AI Tooling: $159,900 - $226,900 * Staff Software Engineer, AI Tooling ...

Factory

Software Engineer, AI

San Francisco, CA · On-site

Software Engineer, AI Responsibilities: Factory is looking for innovative AI Engineers to build and evolve cutting-edge AI systems that transform how software organizations accelerate their ...

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All JobsSoftware Engineer Ai Model Training JobsSoftware Engineer Ai Model Training Jobs in California

Software Engineer Ai Model Training information

What does a software engineer AI model training do?

A Software Engineer specializing in AI Model Training is responsible for designing, developing, and optimizing machine learning models. Their work involves preparing and processing large datasets, selecting appropriate algorithms, implementing training pipelines, and evaluating model performance. They collaborate closely with data scientists and other engineers to ensure that AI models are accurate, efficient, and suitable for deployment in real-world applications. Additionally, they may help maintain infrastructure for model training and contribute to research and development of new AI techniques.

What are the key skills and qualifications needed to thrive as a software engineer AI model training?

To excel as a Software Engineer in AI Model Training, you need strong programming skills (especially in Python), a solid grasp of machine learning fundamentals, and typically a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with data processing tools, and sometimes certifications in AI or ML are highly valuable. Analytical thinking, problem-solving, and effective collaboration enhance your ability to develop and refine complex AI models. These skills ensure that AI solutions are robust, scalable, and aligned with organizational goals in a rapidly evolving technological landscape.

What are some common challenges faced by software engineers AI model training, and how can they be addressed?

Software Engineers focusing on AI model training often encounter challenges such as managing large datasets, ensuring data quality, and optimizing model performance. Addressing these issues typically involves close collaboration with data scientists, domain experts, and DevOps engineers to streamline the data pipeline and refine training processes. Staying up to date with the latest advancements in machine learning frameworks and tools can also help overcome technical hurdles. Regular code reviews and cross-functional meetings further support problem-solving and foster a productive work environment.

What is the difference between Software Engineer Ai Model Training vs Data Scientist?

AspectSoftware Engineer Ai Model TrainingData Scientist
Required CredentialsBachelor's in CS, related field; experience with ML frameworksBachelor's or higher in CS, statistics, or related field; strong analytical skills
Work EnvironmentDevelopment teams, AI labs, cloud platformsData analysis, research environments, business units
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting

While both roles involve working with data and machine learning, Software Engineer Ai Model Training focuses on developing and optimizing AI models through coding and engineering practices. Data Scientists analyze data, build models, and generate insights. The roles often collaborate but differ in their core responsibilities and skill sets.

Can I get paid to train AI models?

Yes, software engineers and AI specialists can be paid to train AI models, especially in roles that involve developing, fine-tuning, and optimizing machine learning algorithms. These positions often require knowledge of programming languages like Python, experience with machine learning frameworks, and access to computational resources. Compensation varies based on experience, location, and the complexity of the models being trained.

How to become a software engineer AI model trainer?

To become a software engineer AI model trainer, you should have a strong background in computer science, programming skills in languages like Python, and experience with machine learning frameworks such as TensorFlow or PyTorch. Gaining knowledge in data preprocessing, model evaluation, and working with large datasets is essential, along with relevant certifications or advanced degrees in AI or related fields.

What are popular job titles related to Software Engineer Ai Model Training jobs in California?

For Software Engineer Ai Model Training jobs in California, the most frequently searched job titles are:

What job categories do people searching Software Engineer Ai Model Training jobs in California look for?

The top searched job categories for Software Engineer Ai Model Training jobs in California are:

What cities in California are hiring for Software Engineer Ai Model Training jobs?

Cities in California with the most Software Engineer Ai Model Training job openings:

Software Engineer Ai Model Training jobs near you
Infographic showing various Software Engineer Ai Model Training job openings in California as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 18% Part Time, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

Machine Learning Engineer, Reinforcement Learning (San Francisco)

Skild AI

San Francisco, CA • On-site

$300K/yr

Full-time

Re-posted 23 days ago

Job description

Get AI-powered advice on this job and more exclusive features.

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.

Company Overview

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.


Responsibilities

  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.

  • Design and conduct experiments to train RL models and conduct real-world tests.

  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.

  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.

  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.

  • Stay up-to-date with the latest research and advancements in reinforcement learning.


Preferred Qualifications

  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.

  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.

  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).

  • Strong background in algorithms, data structures, and software engineering principles.

  • Experience with physics simulation engines and tools for training RL.

  • Deep understanding of state-of-the-art machine learning techniques and models.

  • Extensive industry experience with reinforcement learning and robotic systems.

Base Salary Range: $100,000 USD - $300,000 USD

Seniority level
  • Seniority levelEntry level
Employment type
  • Employment typeFull-time
Job function
  • Job functionEngineering and Information Technology
  • IndustriesSoftware Development

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