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Assistant Llm Trainer Jobs (NOW HIRING)

Luminary Cloud

LLM Engineer

San Mateo, CA · On-site

... next generation of intelligent assistants for engineering workflows. You'll work at the ... Connect LLM capabilities with Luminary's Physics AI training/evaluation/inference pipelines ...

BC Forward

Linguist

California, MD · On-site

$35 - $40/hr

Develop and maintain annotation schemas and guidelines for LLM training data, including instruction ... Support programmatic methods for generating synthetic annotated data at scale. Assist in model ...

Agoda

Technical Product Manager, LLM/ML Domain

Boston, MA · On-site

$181K - $209K/yr

... training, and internal evangelism • Collaborate with engineering to level up Agoda's platforms to ... assistants and autonomous agents • Ensure platform APIs, tooling, and abstractions enable ...

Agoda

Technical Product Manager, LLM/ML Domain

Manhattan, NY · On-site

$183K - $212K/yr

... training, and internal evangelism • Collaborate with engineering to level up Agoda's platforms to ... assistants and autonomous agents • Ensure platform APIs, tooling, and abstractions enable ...

Agoda

Technical Product Manager, LLM/ML Domain

Los Angeles, CA · On-site

$179K - $208K/yr

... training, and internal evangelism • Collaborate with engineering to level up Agoda's platforms to ... assistants and autonomous agents • Ensure platform APIs, tooling, and abstractions enable ...

MSRCosmos

AI Solution Architect

Bellevue, WA · On-site

$71 - $93.75/hr

... assistants LLM APIs prompt engineering costperf controls Azure AI Search vector search hybrid retrieval custom scoring reranking Azure ML training deployment model registry pipelines Cognitive ...

Texas State Library and Archives Commision

AI Architect

$65 - $84.75/hr

... assistants LLM APIs prompt engineering costperf controls Azure AI Search vector search hybrid retrieval custom scoring/reranking Azure ML training deployment model registry pipelines Cognitive ...

Adobe

Principal Product Manager

San Jose, CA · On-site

... assistant/LLM entry points. What you'll bring * 10+ years in Product Management with 3+ years ... Enterprise empathy: you can balance rapid iteration with stability, change-management, and training ...

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Assistant Llm Trainer information

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How much do assistant llm trainer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for assistant llm trainer in the United States is $42,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $24,000.00 and $50,500.00 per year, depending on experience, location, and employer.

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

To thrive as an Assistant LLM Trainer, you need a solid understanding of machine learning concepts, natural language processing, and a relevant degree in computer science or a related field. Familiarity with Python, deep learning frameworks like TensorFlow or PyTorch, and experience with data annotation tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills help in refining data quality and collaborating with cross-functional teams. These skills are crucial for developing high-quality language models and ensuring the success of AI-driven projects.

What are Assistant LLM Trainers?

Assistant LLM Trainers are professionals who help develop, train, and fine-tune large language models (LLMs) used in artificial intelligence applications. They assist in tasks such as data collection, annotation, model evaluation, and iterative improvement of AI models. Their work ensures that LLMs become more accurate, ethical, and aligned with user expectations. Assistant LLM Trainers often collaborate with data scientists, engineers, and research teams to provide feedback and improve model performance.

What are some common challenges faced by Assistant LLM Trainers when preparing data for model training?

Assistant LLM Trainers often face challenges related to data quality and consistency, as preparing large and diverse datasets for language model training requires careful attention to annotation guidelines and error checking. Balancing the need for comprehensive, unbiased data with tight deadlines can also be demanding. Additionally, effective collaboration with data scientists and senior trainers is essential to ensure that the datasets align with project goals and meet technical standards. Over time, this experience helps build strong analytical and teamwork skills, which are valuable for career advancement in AI and machine learning roles.
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Assistant Llm Trainer jobs near you

Senior Software Engineer - LLM Trainer

Kake Group

San Francisco, CA • Remote

$125K - $165K/yr

Contractor

Re-posted 18 days ago

Job description

We are looking for a Senior Software Engineer to contribute to the development and evaluation of AI training data for a leading expert human data platform for AI agents and LLMs.

In this role, you will work at the intersection of software engineering and artificial intelligence, helping AI labs and companies build better, safer, and more capable models. You will leverage your deep technical expertise to write prompts, produce reference-quality code solutions, evaluate model outputs, and provide the structured human signal that makes AI systems smarter.

This is not a traditional engineering role - it is a unique opportunity for senior engineers who want to shape how the next generation of AI understands, generates, and reasons about code.

Key Responsibilities

  • Create and review coding tasks based on real-world software engineering scenarios, including debugging, refactoring, code generation, API usage, automated tests, performance, security, and edge cases.
  • Write high-quality reference solutions that are correct, clear, testable, and aligned with task requirements.
  • Evaluate AI-generated code and responses using structured rubrics, assessing correctness, clarity, security, performance, maintainability, and instruction-following.
  • Compare multiple model responses, select the strongest answer, and justify your decision with clear technical reasoning.
  • Identify bugs, hallucinated APIs, missing edge cases, weak explanations, and poor engineering decisions in AI-generated outputs.
  • Work with terminal-based development workflows when needed, including running tests, debugging issues, managing dependencies, and navigating repositories.
  • Follow detailed guidelines consistently and participate in calibration activities to ensure high-quality, reliable evaluations.

Core Requirements

  • 5+ years of professional software engineering experience in a backend, fullstack, or systems role.
  • Strong proficiency in at least one core programming language, ideally Python, JavaScript/TypeScript, Go, Java, C++, or SQL.
  • Hands-on experience with Terminal-Bench, with the ability to evaluate AI agent performance on terminal-based tasks including compiling code, running tests, managing environments, and completing multi-step software engineering workflows.
  • Comfortable working with Git, command line/terminal, and common development workflows.
  • Ability to evaluate code critically - not only whether it works, but whether it is well-designed, secure, and maintainable.
  • Prior experience in AI data production, RLHF, data annotation, or LLM evaluation projects.
  • Excellent written and verbal communication skills in English.
  • Ability to work independently in a remote, asynchronous, fast-paced environment.
  • High attention to detail and the ability to follow complex, rubric-based guidelines consistently

Nice-to-Have

  • Experience with Python-heavy workflows, automated testing frameworks, Docker, Linux, bash, or containerized environments.
  • Experience with repo-level code reasoning, large codebases, or open-source contributions.
  • Background in backend systems, data engineering, DevOps, infrastructure, security, or large codebase.

Additional

- US Timezone Overlap: PST (GMT -8)

Please Note: Due to the high volume of applications, only shortlisted candidates will be contacted.

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.