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Remote Llm Researcher Jobs (NOW HIRING)

Horizon3.ai

Staff Attack Engineer, AI/LLM

Get to Know Us Horizon3.ai is a fast-growing, remote cybersecurity company dedicated to the mission ... Research and apply model and supply chain attacks (poisoning, training data extraction, adversarial ...

Nvidia

$135K - $181K/yr

Deep understanding of memory hierarchies (GPU HBM, host DRAM, SSD, and remote/object storage) and ... Excellent communication skills and prior experience leading cross-functional efforts with research ...

Prolific

Forward Deployed Researcher

Strong knowledge of LLM evaluation methodologies, data collection design, and human feedback ... Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Governance, Privacy and Security Lab is conducting research at the intersection of security ...

USM

JB061755 - AI Prompt Engineer - Remote

This is for a healthcare research client and looking for candidates who are located preferably in ... LLM, LLM instructions * Build and Test AI workflows * AI Experience - Perplexity, ChatGPT or ...

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All JobsRemote Llm Researcher Jobs

Remote Llm Researcher information

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$30K

$113.1K

$164.5K

How much do remote llm researcher jobs pay per year?

As of Jul 5, 2026, the average yearly pay for remote llm researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote LLM Researcher, and why are they important?

To thrive as a Remote LLM Researcher, you need a strong background in machine learning, natural language processing, and deep learning, typically supported by an advanced degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience working with large language models (LLMs), and knowledge of distributed computing tools are commonly required. Outstanding problem-solving abilities, communication skills, and the ability to work independently are essential soft skills for remote collaboration and research innovation. These skills enable effective development, evaluation, and deployment of advanced language models in a distributed team environment.

How do Remote LLM Researchers typically collaborate with cross-functional teams given their distributed work environment?

Remote LLM Researchers often work closely with data scientists, machine learning engineers, and product managers via virtual collaboration tools such as Slack, Zoom, and GitHub. Regular meetings, shared documentation, and project management platforms help maintain clear communication and alignment on research goals. Being proactive in sharing updates, seeking feedback, and participating in code reviews is essential for seamless teamwork. This collaborative approach ensures research findings can be effectively integrated into products and services, despite the physical distance.

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

AspectRemote Llm ResearcherRemote Data Scientist
CredentialsAdvanced degrees in AI, NLP, or related fields; research experienceDegree in Data Science, Statistics, or Computer Science; often includes certifications
Work EnvironmentResearch-focused, often in AI labs or tech companies, remote options availableData analysis, modeling, and visualization tasks, remote or on-site
Industry UsageAI research, NLP development, machine learning innovationBusiness analytics, predictive modeling, data-driven decision making

Remote Llm Researchers focus on developing and improving large language models through research and experimentation, often in AI labs. Remote Data Scientists analyze data to generate insights and build predictive models. While both roles require strong technical skills, Remote Llm Researchers are more research-oriented, whereas Remote Data Scientists focus on applying data techniques to solve business problems.

What is a Remote LLM Researcher?

A Remote LLM Researcher is a professional who studies and develops large language models (LLMs), such as GPT or BERT, while working from a location outside of a traditional office setting. Their work typically involves conducting experiments, analyzing data, improving model architectures, and publishing findings in the field of natural language processing (NLP). Remote LLM Researchers often collaborate with colleagues online, use cloud-based computing resources, and contribute to advancements in AI language technologies. This role requires strong programming skills, a background in machine learning, and the ability to work independently in a distributed team environment.
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Remote Llm Researcher jobs near you
Infographic showing various Remote Llm Researcher job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.
Machine Learning Engineer (LLM / Personalization)

Machine Learning Engineer (LLM / Personalization)

Qloo

New York, NY • On-site, Remote

$100K - $120K/yr

Full-time

Medical, Retirement, PTO

Posted 21 days ago

Job description

About Us

At Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data-over half a billion records of public figures, places, music artists, media, brands, and more, plus a globe-spanning consumer behavior and sentiment database-to unearth deep insights about consumer preferences.

From understanding global travel trends to curating the perfect restaurant recommendation based on your unique tastes, our Taste AI engine sifts through the noise to find the signals that matter.

And the best part? Qloo's API suite is powered by cultural entities, not personal identities-ensuring our insights are derived without relying on personally identifiable information.

As we expand our investment in LLMs and AI agents, we are building the next generation of intelligent systems that combine generative models with structured taste intelligence-bringing reliability, explainability, and real-world grounding to AI applications.

Role Overview

As a Machine Learning Engineer reporting to the LLM Research Lead, you will operate at the intersection of large language models, recommendation systems, and Qloo's proprietary taste graph.

You will work closely with Research and Data Engineering teams to design and deploy systems that integrate LLMs with structured cultural intelligence. This includes building production-ready ML systems, experimenting with new model architectures, and developing novel approaches to grounding generative AI in real-world data.

This role is ideal for someone who enjoys both research-adjacent work and shipping production systems-and wants to shape how LLMs interact with structured knowledge at scale.

Responsibilities
  • Design, build, and deploy machine learning models and systems that power personalization, recommendation, and taste understanding

  • Develop and productionize LLM-powered features, including retrieval-augmented generation (RAG), agent workflows, and prompt / tool orchestration

  • Integrate LLMs with Qloo's structured entity graph and embedding systems to improve accuracy, relevance, and explainability

  • Experiment with and evaluate modern ML approaches (transformers, embedding models, ranking systems, hybrid recommenders)

  • Collaborate with Data Engineering to leverage large-scale datasets for LLM pipelines

  • Contribute to model evaluation frameworks and optimize model performance, cost, and latency in production environments

  • Stay up-to-date with the latest advancements in LLMs, recommendation systems, and applied ML-and bring those insights into production

Qualifications

  • Strong experience in Python and machine learning frameworks (e.g., PyTorch, CUDA, Metaflow/Kubeflow, etc)

  • Experience working with large language models (LLMs), including APIs (OpenAI, Anthropic, etc) and/or open-source models (Hugging Face)

  • Familiarity with retrieval systems, embeddings, vector search, or recommendation systems

  • Experience building and deploying ML systems in production environments

  • Solid understanding of data pipelines (Airflow) and working with large-scale datasets (e.g., Spark, S3, SQL)

  • Experience with AWS or similar cloud platforms

  • Experience working in AI-native development workflows, including heavy use of tools like Claude Code, Cursor, or similar

  • Strong problem-solving skills and ability to work across both research and engineering domains

  • Prior experience in a startup or fast-paced environment

We Offer
  • Competitive salary and benefits package, including health insurance, retirement plan, and paid time off

  • The opportunity to shape how LLMs and structured data systems work together in real-world applications

  • A collaborative, low-ego work environment where your ideas are valued and your contributions are visible

  • Direct exposure to cutting-edge work at the intersection of generative AI and large-scale recommendation systems

  • Flexible work arrangements (remote and hybrid options) and a healthy respect for work-life balance

$100,000 - $120,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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