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Remote Llm Trainer Jobs (NOW HIRING)

Principal Machine Learning Engineer

Boston, MA · On-site +1

$189.60K - $312.73K/yr

You will collaborate with our technical and research teams to develop LLM training and deployment ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

... • Proven LLM red-teaming / adversarial testing experience (required) • Strong ability to ... in a remote contractor environment • Secure handling of sensitive and confidential content ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$174.19K - $287.41K/yr

You will collaborate with our technical and research teams to develop LLM training and deployment ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

Tamil Translator (Remote) | Sigma AI

$45K - $58.90K/yr

... or LLM training * Strong attention to detail What will you do? Annotation - Audio/Video/Image ... remote , performed through an online platform available 24/7. This opportunity is offered for ...

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Remote Llm Trainer information

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$15

$36

$92

How much do remote llm trainer jobs pay per hour?

As of May 29, 2026, the average hourly pay for remote llm trainer in the United States is $36.91, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $52.88 per hour, depending on experience, location, and employer.

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

To thrive as a Remote LLM Trainer, you need a deep understanding of machine learning, natural language processing, and large language models, typically supported by a degree in computer science or related fields. Experience with Python, deep learning frameworks like TensorFlow or PyTorch, and familiarity with annotation tools or data labeling platforms is essential. Strong communication, attention to detail, and the ability to work independently are standout soft skills in this role. These skills and qualities ensure accurate model training, effective collaboration with distributed teams, and the delivery of high-quality AI solutions.

What does a typical workday look like for a Remote LLM Trainer, and how do they collaborate with team members?

As a Remote LLM Trainer, your workday often involves creating, curating, and reviewing datasets, developing prompts, and evaluating large language model outputs for quality and safety. Much of your collaboration happens asynchronously through digital channels—such as project management tools, messaging platforms, and regular video meetings—with researchers, data scientists, and fellow trainers. You may also participate in feedback sessions to discuss model behavior and share insights on improving training methodologies. Adapting to rapidly evolving project requirements and maintaining clear communication are key to success in this distributed, fast-paced environment.

What are Remote LLM Trainers?

Remote LLM Trainers are professionals who work from any location to help train large language models (LLMs) by providing high-quality data, evaluating model outputs, and refining model behavior. They may annotate data, review AI-generated content, or design prompts and tasks to improve the model's performance. These roles are crucial in ensuring that LLMs become more accurate, safe, and useful across various applications. Remote LLM Trainers often have backgrounds in language, linguistics, data science, or related fields and rely on digital tools to collaborate with AI development teams.

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

AspectRemote Llm TrainerData Scientist
Required CredentialsBackground in AI, NLP, or machine learning; often a degree in computer science or related fieldDegree in computer science, statistics, or related fields; often certifications in data analysis or machine learning
Work EnvironmentRemote, collaborative teams developing and fine-tuning language modelsRemote or on-site, analyzing data, building models, and deriving insights
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting, and research organizations

While both roles involve working with data and machine learning, a Remote Llm Trainer specializes in training and refining language models, whereas a Data Scientist focuses on analyzing data, building predictive models, and deriving insights across various industries.

More about Remote Llm Trainer jobs
What cities are hiring for Remote Llm Trainer jobs? Cities with the most Remote Llm Trainer job openings:
What are the most commonly searched types of Llm Trainer jobs? The most popular types of Llm Trainer jobs are:
What states have the most Remote Llm Trainer jobs? States with the most job openings for Remote Llm Trainer jobs include:

Principal Machine Learning Engineer

Redhat

Boston, MA • On-site, Remote

$189.60K - $312.73K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


Job description

Job Summary

At Red Hat we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs and vLLM to every enterprise. Red Hat AI Inference team accelerates AI for the enterprise and brings operational simplicity to GenAI deployments. As leading developers, maintainers of the vLLM project, and inventors of state-of-the-art techniques for model quantization and sparsification, our team provides a stable platform for enterprises to build, optimize, and scale LLM deployments.

As a Machine Learning Engineer focused on model optimization algorithms, you will work closely with our product and research teams to develop SOTA deep learning software. You will collaborate with our technical and research teams to develop LLM training and deployment pipelines, implement model compression algorithms, and productize deep learning research. If you are someone who enjoys bridging research and production, optimizing large models, and contributing to open-source AI tooling, this role is for you.

Join us in shaping the future of AI!

What you will do
  • Contribute to the design, development, and testing of various inference optimization algorithms in the LLM-compressor, Speculators, and vLLM projects.

  • Design, implement, and optimize model compression pipelines using techniques such as quantization and pruning.

  • Develop and maintain speculative decoding frameworks to improve inference speed while maintaining model accuracy.

  • Collaborate closely with research scientists to translate experimental ideas into robust, production-ready systems

  • Profile and optimize end-to-end LLM performance, including memory usage, latency, and throughput

  • Benchmark, evaluate, and implement strategies for optimal performance on target hardware

  • Build tools to streamline model training, evaluation, and deployment.

  • Participate in technical design discussions and propose innovative solutions to complex problems

  • Contribute to open-source projects, code reviews, and documentation; collaborate with internal and external contributors.

  • Mentor and guide team members, fostering a culture of continuous learning and innovation.

  • Stay current with LLM architectures, inference optimizations, quantization research, and CPU/GPU hardware advancements.

What you will bring
  • Strong understanding of machine learning and deep learning fundamentals with experience in one or more of LLM Inference Optimizations and NLP

  • Experience with tensor math libraries such as PyTorch and NumPy

  • Strong programming skills with proven experience implementing Python based machine learning solutions

  • Ability to develop and implement research ideas and algorithms

  • Experience with mathematical software, especially linear algebra

  • Understanding of Linear Algebra, Gradients, Probability, and Graph Theory

  • Strong communications skills with both technical and non-technical team members

  • BS, or MS in computer science or computer engineering or a related field. A PhD in a ML related domain is considered a strong plus.

#LI-MD2

#AI-HIRING

#vllm-1

The salary range for this position is $189,600.00 - $312,730.00. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat's compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.

About Red Hat

Red Hat is the world's leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Benefits
Comprehensive medical, dental, and vision coverage
Flexible Spending Account - healthcare and dependent care
Health Savings Account - high deductible medical plan
Retirement 401(k) with employer match
Paid time off and holidays
Paid parental leave plans for all new parents
Leave benefits including disability, paid family medical leave, and paid military leave
Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States.

Inclusion at Red Hat
Red Hat's culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.


Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email application-assistance@redhat.com. General inquiries, such as those regarding the status of a job application, will not receive a reply.