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Llm Remote Jobs (NOW HIRING)

Near AI

LLM Inference Engineer

OR · 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 ...

Near AI

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 ...

Horizon3.ai

Staff Attack Engineer, AI/LLM

Get to Know Us Horizon3 is a fast-growing, remote cybersecurity company dedicated to the mission of ... Essential Functions Attacking AI/LLM Systems * Break AI and agentic systems and translate that ...

Digital Links Inc

AI LLM (W2)

Glen Allen, VA · Remote

Remote Work Requirements AI LLM GC/USC Work must be performed from a secure, fixed location with reliable high-speed internet within the contiguous United States. Interview Process Our process is ...

Nvidia

$135K - $181K/yr

Design and evolve a unified memory layer that spans GPU memory, pinned host memory, RDMA-accessible memory, SSD tiers, and remote file/object/cloud storage to support large-scale LLM inference.

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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 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 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 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.
More about Llm Remote jobs
What cities are hiring for Llm Remote jobs? Cities with the most Llm Remote job openings:
What are the most commonly searched types of Llm jobs? The most popular types of Llm jobs are:
What states have the most Llm Remote jobs? States with the most job openings for Llm Remote jobs include:
What job categories do people searching Llm Remote jobs look for? The top searched job categories for Llm Remote jobs are:
Llm Remote jobs near you
Infographic showing various Llm Remote job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 3% As Needed, 91% Full Time, 1% Part Time, 2% Contract, and 2% Nights. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.

LLM Inference Engineer

Near AI

OR • On-site, Remote

Other

Posted 29 days ago

Job description

Locations: San Francisco or Remote

About The Role

The NEAR AI team is building decentralized and confidential machine learning infrastructure to enable user-owned AI. Our mission is to build highly scalable and efficient infrastructure for open-source AI at a global scale.

We are specifically seeking an expert in high-performance LLM serving systems and inference optimization. In this role, you will push the boundaries of how large language models are served.

What You'll Be Doing

  • Architect and maintain production high-traffic LLM serving systems.
  • Optimize throughput, latency, and cost for leading open-source LLMs.

What We're Looking For

  • Strong hands-on experience in LLM inference, with expertise debugging and optimizing major inference engines such as SGLang, vLLM, or TensorRT.
  • Deep knowledge of state-of-the-art GPU architectures, and effectively exploit them using PyTorch, Triton, CuTe, CUDA, etc.
  • Proven track record in designing and maintaining end-to-end high-traffic LLM serving systems.
  • Strong problem-solving skills and ability to communicate technical ideas clearly.

We'd Love If You Have

  • Experience with Trusted Execution Environments (TEE).
  • Active contributor to open-source LLM inference engines.

Please let us know if you require any special requirements for your interview and we'll do our best to accommodate.

Apply