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Remote Training Ai Models Jobs in California (NOW HIRING)

Cerebras Systems

$148K - $196K/yr

This architecture allows Cerebras to deliver industry-leading training and inference speeds; over ... Remote possible for candidates willing to travel 1-2x per quarter. Why Join Cerebras People who are ...

YO AI Labs

AI Consulting Expert - Remote

San Jose, CA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Develop, refine, and evaluate prompts for AI models. * Conduct quality assurance and rubric-based ...

YO AI Labs

AI Consulting Expert - Remote

Palo Alto, CA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Develop, refine, and evaluate prompts for AI models. * Conduct quality assurance and rubric-based ...

YO AI Labs

AI Consulting Expert - Remote

Los Angeles, CA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Develop, refine, and evaluate prompts for AI models. * Conduct quality assurance and rubric-based ...

YO AI Labs

AI Consulting Expert - Remote

San Francisco, CA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Develop, refine, and evaluate prompts for AI models. * Conduct quality assurance and rubric-based ...

Biohub

Staff Research Scientist, AI Safety

Redwood City, CA · On-site +1

$241K - $301K/yr

Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency ...

YO AI Labs

AI Data Science Expert - Remote

San Jose, CA · Remote

$100 - $200/hr

Develop, optimize, and evaluate prompts to improve AI model performance. * Conduct rubric-based ... Annotate data and support quality assurance initiatives for AI training. * Interpret complex ...

YO AI Labs

AI Data Science Expert - Remote

Palo Alto, CA · Remote

$100 - $200/hr

Develop, optimize, and evaluate prompts to improve AI model performance. * Conduct rubric-based ... Annotate data and support quality assurance initiatives for AI training. * Interpret complex ...

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Remote Training Ai Models information

What does it mean to work in remote training of AI models?

Working in remote training of AI models involves creating, refining, and improving artificial intelligence systems from a remote location. This typically includes tasks like labeling data, reviewing machine learning outputs, or providing feedback on model accuracy. Remote AI trainers often use specialized tools or platforms to help teach models how to interpret data, such as images, text, or audio. The work can be done from anywhere with an internet connection, making it flexible for many people. These roles are essential for ensuring AI systems learn correctly and perform well in real-world scenarios.

What are the key skills and qualifications needed to thrive as a remote AI model trainer?

To thrive as a Remote AI Model Trainer, you need strong analytical skills, attention to detail, and familiarity with data annotation or labeling, often supported by a background in computer science or a related field. Experience with data management tools, annotation platforms, and sometimes basic programming (such as Python) is typically required. Clear communication, reliability, and the ability to work independently are standout soft skills in this remote role. These abilities ensure high-quality data preparation, which is critical for developing accurate and effective AI models.

What are some common challenges faced when working remotely to train AI models, and how can they be overcome?

One of the main challenges in remote AI model training roles is maintaining clear communication with teams across different time zones and ensuring alignment on project goals. Additionally, remote data security and managing large datasets can be complex without in-person collaboration. To overcome these challenges, it's helpful to establish regular video check-ins, use project management tools, and follow secure data-sharing protocols. Cultivating proactive communication and staying organized can help remote AI trainers stay productive and connected with their teams.

What is the difference between Remote Training Ai Models vs Data Scientist?

AspectRemote Training Ai ModelsData Scientist
Required CredentialsKnowledge of AI/ML frameworks, programming skills, understanding of data preprocessingStatistics, programming, data analysis, often a degree in related fields
Work EnvironmentRemote, collaborative with AI/ML teams, cloud platformsRemote or on-site, research-focused, cross-industry
Industry UsageAI development, machine learning model training, deploymentData analysis, predictive modeling, business insights

Remote Training Ai Models primarily focus on developing and training machine learning models remotely, often requiring programming and AI-specific skills. Data Scientists analyze data to generate insights and build models, with a broader focus on data analysis. While both roles may work remotely and require technical expertise, Remote Training Ai Models are specialized in AI model training, whereas Data Scientists have a wider scope in data analysis and interpretation.

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

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

Remote Training Ai Models jobs near you

Senior Product Manager, AI Models

Cerebras Systems

On-site, Remote

$148K - $196K/yr

Full-time

Posted 9 days ago

Job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Own the Future of AI Inference
Cerebras powers the world's fastest AI inference. As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our product - deciding which models ship, how they perform, and how the world discovers them.
You'll partner directly with leading AI labs, drive launches that shape the industry, and ensure every model on our platform delivers exceptional quality at unprecedented speed.
What You'll Own
Strategic Model Portfolio
  • Own the models roadmap: decide which frontier and open-source models we support based on market demand, research trends, and strategic fit
  • Establish partnerships with top model labs, for day0 launches
  • Build relationships with open-source maintainers to accelerate community model adoption

Product Quality & Customer Success
  • Define and enforce quality standards across our model catalog through systematic evaluation frameworks
  • Design benchmarks and evaluations that prove our models deliver production-grade performance
  • Own the feedback loop: gather customer insights, identify model weaknesses, and drive improvements with engineering
  • Enable strategic customers to integrate our inference into their products-removing blockers and optimizing for their specific use cases

Go-to-Market Excellence
  • Lead high-impact model launches that generate buzz and adoption
  • Create compelling product marketing: demos, benchmarks, tutorials, and documentation that showcase what's possible on Cerebras
  • Craft technical content that resonates with developers and decision-makers alike

Technical Decision-Making
  • Select and prioritize performance optimizations (quantization, speculative decoding, etc.) based on customer needs and hardware capabilities
  • Collaborate with optimization engineers to implement techniques that maximize our speed advantage
  • Balance tradeoffs between quality, latency, throughput, and cost

Cross-Functional Leadership
  • Orchestrate launches across model enablement, optimization engineering, deployment, sales, and marketing
  • Drive alignment in a fast-moving environment where priorities shift based on model releases and customer needs
  • Be the voice of the customer to engineering and the voice of product to customers

Skills & Qualifications
What we need to see:
  1. 5+ years of experience as a product manager, currently at or above the level of Senior PM.
  2. 5+ years of total technical work experience (e.g. SWE, ML researcher, solution engineer).
  3. Ability to thrive in a fast-paced, dynamic environment. With an entrepreneurial sense of ownership and ability to lead projects.
  4. Knowledge and passion for the worlds of open-source models and generative AI research.
  5. Knowledge of the community model ecosystem, including: PyTorch, Hugging Face, vLLM, and SGLang.
  6. Highly motivated, independent, organized, and an effective communicator.
  7. Comfortable using Python with the chat completions API, for basic model testing.

Preferred requirements
How to stand out:
  1. Product manager experience at a model training lab or a company that implements open-source models.
  2. Experience working with customers in a solution engineering role.
  3. Experience writing technical marketing assets and social media, with a growing portfolio.
  4. Experience working in a cross-functional organization, and leading projects across multiple teams.
  5. Experience writing model quality evaluations and system prompt harnesses.
  6. Experience writing application code in use cases such as code generation or deep research search application.
  7. Expertise on agentic flows and current LLM model family architectures.
  8. Understanding of model compilers and optimization.
  9. Contributor to communities like vLLM, SGLang, PyTorch, or Hugging Face transformers.
  10. Experience with model optimization or compression methods like quantization.

Location
  • Hybrid at our Sunnyvale, California or Toronto, Canada office.
  • Remote possible for candidates willing to travel 1-2x per quarter.

Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we've reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
  1. Build a breakthrough AI platform beyond the constraints of the GPU.
  2. Publish and open source their cutting-edge AI research.
  3. Work on one of the fastest AI supercomputers in the world.
  4. Enjoy job stability with startup vitality.
  5. Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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