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Llm Remote Jobs in California (NOW HIRING)

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LLM Inference Engineer

San Francisco, CA · On-site +1

San Francisco or Remote About The Role The NEAR AI team is building decentralized and confidential ... We are specifically seeking an expert in high-performance LLM serving systems and inference ...

Mercor

AI Red Team Specialist - LLM

San Francisco, CA · On-site +1

$60 - $90/hr

Remote Commitment: 35 hours/week Role Responsibilities * Probe models to explore how frontier AI models handle coding , ML , and analysis tasks. Identify spots where models quietly fail. * Design ...

Mercor

LLM Agent Engineer - Production

San Francisco, CA · Remote

$100 - $500/hr

Remote Role Responsibilities * Build and operate LLM agents in production environments. * Evaluate agent performance and determine improvements after changes. * Manage long-running agents, including ...

YO AI Labs

GPU Programmer - Remote

San Francisco, CA · Remote

$60 - $85/hr

Remote Job Overview We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU ...

YO AI Labs

GPU Programmer - Remote

San Francisco, CA · Remote

$60 - $85/hr

Remote Job Overview We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU ...

YO AI Labs

GPU Programmer - Remote

Los Angeles, CA · Remote

$60 - $85/hr

Remote Job Overview We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU ...

YO AI Labs

GPU Programmer - Remote

San Jose, CA · Remote

$60 - $85/hr

Remote Job Overview We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU ...

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Llm Remote information

What is an llm remote job?

An LLM Remote job typically refers to a position that involves working with large language models (LLMs) such as OpenAI's GPT, but done remotely rather than in a traditional office setting. These roles can include positions like machine learning engineer, data scientist, prompt engineer, or AI researcher, all focused on developing, fine-tuning, or applying LLMs. Working remotely allows professionals to contribute to AI projects from anywhere, often collaborating with distributed teams and leveraging cloud-based tools. This flexibility is ideal for those who want to work in the AI field without relocating to a tech hub.

What are the key skills and qualifications needed to thrive as an llm remote engineer, and why are they important?

To excel as an LLM Remote Engineer, a solid background in machine learning, natural language processing, and proficiency with programming languages like Python is essential, often supported by a degree in computer science or a related field. Experience with frameworks such as PyTorch or TensorFlow, familiarity with large language models (LLMs), and relevant cloud platforms (like AWS or Azure) are typically required, along with certifications in AI or ML being advantageous. Strong problem-solving, communication, and self-motivation are crucial soft skills for collaborating effectively across remote teams and driving innovation. These competencies ensure successful model development, deployment, and maintenance in a distributed work environment.

What are some common challenges faced by remote large language model (LLM) engineers, and how can they overcome them?

Remote LLM engineers often face challenges such as collaborating effectively across time zones, maintaining clear communication with distributed teams, and staying updated on rapidly evolving AI research. To overcome these obstacles, it's important to leverage collaboration tools (like Slack, GitHub, and video conferencing), establish regular check-ins, and participate in virtual knowledge-sharing sessions. Additionally, proactively seeking feedback and engaging with global AI communities can help remote LLM engineers stay aligned with team goals and industry trends.

What is the difference between Llm Remote vs Legal Assistant?

AspectLlm RemoteLegal Assistant
Required CredentialsLaw degree (JD or equivalent), bar admission (preferred)High school diploma or associate degree, paralegal certification often preferred
Work EnvironmentRemote, flexible hours, legal firms or corporate legal departmentsOffice-based or hybrid, law firms, corporate legal departments
Industry UsageLegal research, document review, legal analysisLegal support, document preparation, client communication
Search & Comparison IntentUnderstanding remote legal roles, legal research jobsLegal support roles, paralegal or legal assistant positions

While both roles support legal operations, Llm Remote typically involves legal research and analysis requiring a law degree, often performed remotely. Legal Assistants focus on administrative and support tasks, usually in-office or hybrid, with less emphasis on legal research. The choice depends on your credentials and preferred work environment.

What are the most commonly searched types of Llm jobs in California?

The most popular types of Llm jobs in California are:

What are popular job titles related to Llm Remote jobs in California?

For Llm Remote jobs in California, the most frequently searched job titles are:

What job categories do people searching Llm Remote jobs in California look for?

The top searched job categories for Llm Remote jobs in California are:

What cities in California are hiring for Llm Remote jobs?

Cities in California with the most Llm Remote job openings:

Llm Remote jobs near you
Infographic showing various Llm Remote job openings in California as of August 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution.

Software Engineer - AI/ML & LLM - Remote

YO AI Labs

San Francisco, CA • Remote

$80 - $120/hr

Full-time

Posted 5 days ago

Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.