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Remote Llm Training Jobs (NOW HIRING)

Gnostech LLC

Software Engineer (US-Remote)

OR · On-site +1

Utilize AI-assisted development tools (e.g., LLM coding assistants, code analysis tools) to enhance ... Familiarity with the AI/ML lifecycle including data preparation, model training, evaluation ...

Vultr

Strategic Technical Account Manager GPU

$115K - $140K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... remote office setup in first year + $400 each following year Internet reimbursement up to $75 per ... You will act as a trusted advisor across LLM training, fine-tuning, RAG workloads, distributed ...

Mutual of Omaha

AI Engineer - Remote

Omaha, NE · Remote

  • Retirement

  • PTO

Improve accuracy by employing systematic experimentation, prompt engineering, data and training ... Guide teams in adopting and building LLM-powered applications, including context engineering ...

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How much do remote llm training jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for remote llm training in the United States is $42.21, according to ZipRecruiter salary data. Most workers in this role earn between $27.88 and $53.85 per hour, depending on experience, location, and employer.

What are common challenges in remote LLM training, and how can they be addressed?

Professionals in remote LLM (Large Language Model) training roles often face challenges such as managing distributed team communication, ensuring data privacy, and handling large-scale computational resources. Staying organized with asynchronous collaboration tools and maintaining clear documentation can help streamline teamwork. Additionally, understanding cloud-based infrastructure and adhering to strict data security protocols are essential for handling sensitive datasets. Regular check-ins and knowledge-sharing sessions also foster a supportive and productive remote work environment.

What is the difference between Remote Llm Training vs Data Scientist?

AspectRemote Llm TrainingData Scientist
Required CredentialsKnowledge of NLP, machine learning, programming skillsStatistics, programming, domain expertise
Work EnvironmentRemote, collaborative teams, AI/ML companiesRemote or on-site, diverse industries
Industry UsageAI development, NLP projectsData analysis, predictive modeling

Remote Llm Training focuses on developing and fine-tuning large language models, requiring expertise in NLP and machine learning. Data Scientists analyze data to extract insights and build models across various industries. While both roles involve programming and data skills, Remote Llm Training is specialized in AI model development, whereas Data Scientists work on broader data analysis tasks.

What is remote LLM training?

Remote LLM training refers to the process of training large language models (LLMs), such as GPT or similar AI models, on distributed computing resources that are accessed remotely. This allows data scientists and AI engineers to leverage powerful hardware, like GPUs or TPUs, which may not be available locally. Remote LLM training is commonly used to handle the massive computational requirements of modern AI models and enables collaboration among teams in different locations. It also provides scalability, flexibility, and cost-effectiveness for organizations working on advanced AI projects.

What skills and qualifications are needed for remote LLM training?

To excel in Remote LLM Training, you need a strong background in machine learning, natural language processing, and computer science, often demonstrated by a relevant degree or industry experience. Familiarity with frameworks like PyTorch or TensorFlow, experience with large-scale data management, and knowledge of distributed computing systems are typically required. Strong problem-solving skills, effective communication, and the ability to work independently are vital soft skills in this remote, collaborative environment. These competencies ensure efficient model training, high-quality output, and seamless teamwork across distributed teams.
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Remote Llm Training jobs near you
Infographic showing various Remote Llm Training job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $87,800 per year, or $42.2 per hour.

AI Benchmark & Datasets Engineer / Researcher

Pathway

Palo Alto, CA • On-site, Remote

Full-time

Re-posted 18 hours ago

Job description

About Pathway
Pathway builds the first post-transformer frontier model that solves AI's fundamental memory problem. While transformers wake up in the same state every time-like Groundhog Day-our architecture enables true continuous learning, infinite context reasoning, and real-time adaptation. We're not optimizing yesterday's technology; we're building what comes after transformers.
Our breakthrough architecture outperforms Transformer and provides the enterprise with full visibility into how the model works. Combining the foundational model with the fastest data processing engine on the market, Pathway enables enterprises to move beyond incremental optimization and toward truly contextualized, experience-driven intelligence. We are trusted by organizations such as NATO, La Poste, and Formula 1 racing teams.
Pathway is led by co-founder & CEO Zuzanna Stamirowska, a complexity scientist who created a team consisting of AI pioneers, including CTO Jan Chorowski who was the first person to apply Attention to speech and worked with Nobel laureate Geoff Hinton at Google Brain, as well as CSO Adrian Kosowski, a leading computer scientist and quantum physicist who obtained his PhD at the age of 20.
The company is backed by leading investors and advisors, including Lukasz Kaiser, co-author of the Transformer ("the T" in ChatGPT) and a key researcher behind OpenAI's reasoning models. Pathway is headquartered in Palo Alto, California.
The Opportunity
You will design and execute rigorous benchmarks and define dataset standards. Collaborating closely with our R&D team, you will build the evaluation infrastructure that guides the evolution of Pathway's post-transformer models.
You Will
  • Proactively identify, prioritize, and curate relevant public and client-driven benchmarks across our target use cases and markets.
  • Evaluate candidate benchmarks for clarity, data quality, evaluation methodology, and fit with our model roadmap.
  • Run benchmarks with baseline models to validate setup, uncover edge cases, and de-risk R&D runs.
  • Hand off "benchmark-ready" packages to R&D (specs, data, evaluation scripts, expected metrics, constraints)
  • Maintain a shared vocabulary and documentation around benchmarks, datasets, and evaluation formats that GTM and R&D can both use.
  • Track and organize benchmark results, model leaderboards, and "what good looks like" for different customers and scenarios.
  • Contribute to demos and public-facing proof points based on benchmark outcomes.

You will play a key role in defining and driving the benchmarking process for AI model evaluation. Your work will directly influence what we build, how we talk about it, and how customers and the market experience BDH.
Requirements
Cover letter
It's always a pleasure to say hi! If you could leave us 2-3 lines, we'd really appreciate that.
You are expected to meet at least one of the following criteria:
  1. You have published at least one paper at NeurIPS, ICLR, or ICML - where you were the lead author or made significant conceptual & code contributions.
  2. You have significantly contributed to an LLM training effort which became newsworthy (topped a Hugging Face benchmark, best in class model, etc.), preferably using multiple GPU's.
  3. You have spent at least 6 months working in a leading Machine Learning research center (e.g. at: Google Brain / Deepmind, Apple, Meta, Anthropic, Nvidia, MILA).
  4. You were an ICPC World Finalist, or an IOI, IMO, or IPhO medalist in High School.
You
  • Have experience with ML/LLM evaluation, data science, or technical product roles, ideally around benchmarks or experimentation.
  • Are comfortable reading papers, leaderboards, and Github repos, and turning them into clear, repeatable benchmark specs.
  • Can talk comfortably with both engineers and customers, and translate between technical detail and business value.
  • Care about high-quality data, reproducible experiments, and crisp documentation
  • Are respectful of others
  • Are fluent in English
Bonus Points
  • Published or open-sourced work on LLM evaluation, benchmarking or data quality.
  • Experience designing custom benchmarks or evaluation protocols for novel model capabilities.

Why You Should Apply
  • Join an intellectually stimulating work environment.
  • Be a pioneer: you get to work with a new type of "Live AI" challenges around long sequences and changing data.
  • Be part of one of an early-stage AI startup that believes in impactful research and foundational changes.

Benefits
  • Type of contract: Full-time, permanent
  • Preferable joining date: Immediate. The positions are open until filled - please apply immediately.
  • Compensation: based on profile and location.
  • Location: Remote work. Possibility to work or meet with other team members in one of our offices: Palo Alto, CA; Paris, France or Wroclaw, Poland. Candidates based anywhere in the EU, UK, United States, and Canada will be considered.

If you meet our broad requirements but are missing some experience, don't hesitate to reach out to us.

Apply