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Remote Large Language Model Llm Jobs (NOW HIRING)

Senior Software Engineer

New York, NY · Remote

$250K - $300K/yr

Develop and integrate large language model (LLM) powered tools to drive the core platform. * Contribute to a high-energy, collaborative, in-person engineering culture centered on moving fast and ...

LLM Prompt Optimization - Design, test, and refine prompts to get high-quality outputs from large language models-ensuring results align with customer goals and industry standards. * Customer ...

The ideal candidate will possess strong full-stack development expertise along with hands-on experience in AI technologies, agentic workflows, prompt engineering, and Large Language Model (LLM ...

Senior AI Systems Engineer

Albuquerque, NM · On-site +1

$95K - $130K/yr

Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI ... This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be ...

LLM Prompt Optimization - Design, test, and refine prompts to get high-quality outputs from large language models-ensuring results align with customer goals and industry standards. * Customer ...

... large language model (LLM) capabilities, and AI infrastructure. Own how models, evaluation ... Fully remote, work from home environment * Employee Share Option Plan * Flexible working hours

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI ... This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be ...

Prior hands-on experience evaluating AI or Large Language Model (LLM) outputs using structured ... Fully remote with flexible working hours. * Project duration may be extended, shortened, or ...

This role is responsible for endtoend frontend and backend development and for integrating AIdriven capabilities such as intelligent automation, AI agents, and large language model (LLM) services ...

This role is responsible for end-to-end front-end and back-end development and for integrating AI-driven capabilities such as intelligent automation, AI agents, and large language model (LLM ...

$19 - $26/hr

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... The successful candidates will assist in developing large language model (LLM) applications for ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... examining how large-language model (LLM)-controlled artificial agents use and develop social ...

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Remote Large Language Model Llm information

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$38

How much do remote large language model llm jobs pay per hour?

As of Aug 2, 2026, the average hourly pay for remote large language model llm in the United States is $24.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $29.09 per hour, depending on experience, location, and employer.

What is a Remote Large Language Model (LLM) job?

A Remote Large Language Model (LLM) job involves working with advanced AI models, like GPT or similar, from a remote location. Professionals in these roles may develop, train, fine-tune, or implement large language models for various applications such as natural language processing, chatbots, or content generation. Remote LLM jobs can include positions like machine learning engineer, research scientist, or AI product manager. The work typically requires strong programming skills, experience with AI frameworks, and the ability to collaborate virtually with global teams.

How does a Remote Large Language Model (LLM) Engineer typically collaborate with cross-functional teams while working remotely?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers through virtual meetings, collaborative coding platforms, and shared documentation tools. Regular communication is key, with daily stand-ups or weekly syncs to align on project goals, update progress, and address challenges. They may also participate in code reviews, contribute to design discussions, and support model deployment efforts, all within a distributed team environment. This remote structure encourages self-motivation and proactive communication to ensure project success.

What are the key skills and qualifications needed to thrive as a Remote Large Language Model (LLM) Engineer, and why are they important?

To thrive as a Remote Large Language Model (LLM) Engineer, you need a strong background in computer science, machine learning, and natural language processing, typically supported by a relevant degree and experience with large-scale models. Proficiency with programming languages like Python, deep learning frameworks such as PyTorch or TensorFlow, and familiarity with cloud platforms and distributed systems are essential. Excellent problem-solving, communication, and collaboration skills are critical for remote teamwork and translating complex requirements into scalable solutions. These skills ensure the effective development, deployment, and maintenance of advanced language models in fast-evolving, distributed environments.

What is the difference between Remote Large Language Model Llm vs Data Scientist?

AspectRemote Large Language Model LlmData Scientist
Required CredentialsAdvanced degrees in AI, NLP, or related fields; experience with machine learning frameworksDegree in Data Science, Statistics, Computer Science, or related fields; strong analytical skills
Work EnvironmentPrimarily remote, focused on developing and fine-tuning language modelsRemote or on-site, analyzing data, building models, and generating insights
Employer & Industry UsageTech companies, AI research labs, startups working on NLP productsTech firms, finance, healthcare, marketing, and research organizations

While both roles involve data and machine learning, a Remote Large Language Model Llm specializes in developing and refining language models, whereas a Data Scientist focuses on analyzing data, building predictive models, and deriving insights across various domains.

More about Remote Large Language Model Llm jobs
What cities are hiring for Remote Large Language Model Llm jobs? Cities with the most Remote Large Language Model Llm job openings:
What are the most commonly searched types of Large Language Model Llm jobs? The most popular types of Large Language Model Llm jobs are:
What states have the most Remote Large Language Model Llm jobs? States with the most job openings for Remote Large Language Model Llm jobs include:
Infographic showing various Remote Large Language Model Llm job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 23% Part Time, 1% Temporary, and 4% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $50,625 per year, or $24.3 per hour.

Post Doctoral Researcher - Multimodal Knowledge Extraction and Reasoning

ExxonMobil

Spring, TX • On-site, Remote

$103K/yr

Full-time

Medical, Life

Posted 3 days ago

New


ExxonMobil rating

5.9

Company rating: 5.9 out of 10

Based on 227 frontline employees who took The Breakroom Quiz

71st of 86 rated oil and gas companies


Job description

About us

At ExxonMobil, our vision is to lead in energy innovations that advance modern living while reducing emissions. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.

The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies. 

We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we can work together.

About the Role

ExxonMobil is seeking a highly motivated Postdoctoral Researcher specializing in multimodal knowledge extraction and reasoning. The successful candidate will develop advanced AI methods to extract, integrate, and reason over information from diverse data sources—including text, images, video, time series, and structured data—to support critical business and engineering decisions.

This role is ideal for a recent Ph.D. graduate with expertise in multimodal machine learning, knowledge representation, and reasoning systems. The candidate will work in a collaborative environment to build next-generation AI systems that transform complex, heterogeneous data into actionable insights.

Key Responsibilities
  • Develop methods for multimodal data fusion and representation learning across text, visual, spatial, and temporal data.
  • Design models for knowledge extraction, including entity recognition, relation extraction, and structured information generation from unstructured and semi-structured data.
  • Build reasoning systems that combine neural methods with symbolic or knowledge-based approaches.
  • Develop and apply large language model (LLM)-based and multimodal foundation models for knowledge understanding and reasoning.
  • Construct and utilize knowledge graphs and structured representations for enhanced reasoning and decision support.
  • Enable context-aware inference and decision-making using heterogeneous data sources.
  • Evaluate models for accuracy, robustness, and reasoning capability, including explainability where relevant.
  • Collaborate with domain experts to translate extracted knowledge into decision-support workflows.
  • Implement scalable pipelines using modern ML frameworks and data engineering best practices.
  • Communicate findings through technical reports, journal publications, and conference presentations.
Example Research Areas
  • Multimodal machine learning and cross-modal representation learning
  • Knowledge extraction from text, images, and sensor data
  • Knowledge graphs and graph-based reasoning
  • Neural-symbolic AI and hybrid reasoning systems
  • Large language models and multimodal foundation models
  • Information retrieval, semantic search, and question answering
  • Temporal and causal reasoning in complex systems
  • Applications to engineering, scientific, and industrial data environments
Required Qualifications
  • Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field, with a focus on multimodal learning, knowledge extraction, or reasoning.
  • Demonstrated research experience in multimodal machine learning and/or knowledge-based AI, including one or more of:
      • Multimodal representation learning
      • Information extraction or natural language understanding
      • Knowledge graphs or structured representations
      • Reasoning systems (neural, symbolic, or hybrid)
  • Experience with modern deep learning architectures, including transformers and foundation models.
  • Strong programming skills in Python.
  • Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Experience working with heterogeneous datasets (text, images, structured data, etc.).
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work effectively in multidisciplinary teams.
Preferred Qualifications
  • Experience with multimodal foundation models or large language models (LLMs).
  • Familiarity with knowledge graph construction, querying, and reasoning frameworks.
  • Experience with retrieval-augmented generation (RAG) or hybrid search systems.
  • Background in probabilistic reasoning, causal inference, or uncertainty-aware AI.
  • Experience with scalable data pipelines and distributed ML systems.
  • Experience applying AI methods to scientific, engineering, or industrial datasets.
  • Strong publication record in multimodal AI, NLP, or knowledge-based systems.
  • Demonstrated ability to translate research into practical decision-support tools.
Duration

This opportunity is for a postdoctoral position expected to last one to three years, subject to annual review and renewal.

Work Location

Our post doctoral research employees are located at our main corporate office in Spring, Texas.

Your Total Rewards

An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life. Individual pay is determined based on various factors including degree/education, discipline, year of study, skills, abilities, qualifications, and work experience. 


More information on our Company’s benefits can be found at www.exxonmobilfamily.com.


Please note pay rates and benefits may be changed from time to time without notice, subject to applicable law.

Relocation Options

Relocation benefits may be available to you based on ExxonMobil eligibility guidelines. 

Equal Opportunity Employer

ExxonMobil is an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability.

Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship. 

Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.


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