1

Assistant Llm Training Jobs (NOW HIRING)

... 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 ...

Apply foundational data science skills to assist in data modeling and the maintenance of automated ... Exposure to Machine Learning concepts and LLM training. * Familiarity with data visualization tools ...

Apply foundational data science skills to assist in data modeling and the maintenance of automated ... Exposure to Machine Learning concepts and LLM training. * Familiarity with data visualization tools ...

These products represent our vision for AI that doesn't just assist engineers, but works alongside ... Deep familiarity with the LLM training pipeline end to end: pre-training data, optimization ...

... assistants (ChatGPT, Claude, Gemini, Copilot, Perplexity). Identify high-value niche queries for M& ... LLM training sets. Manage backlink profile health, including disavowal of toxic links and ...

... assistants (ChatGPT, Claude, Gemini, Copilot, Perplexity). Identify high-value niche queries for M& ... LLM training sets. Manage backlink profile health, including disavowal of toxic links and ...

next page

Showing results 1-20

Assistant Llm Training information

See salary details

$12

$21

$31

How much do assistant llm training jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for assistant llm training in the United States is $21.16, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $22.60 per hour, depending on experience, location, and employer.

What are some typical challenges faced by Assistant LLM Training professionals, and how can they be addressed?

Assistant LLM Training professionals often encounter challenges such as ensuring high-quality data annotation, managing large and complex datasets, and keeping up with evolving model requirements. Effective communication with data scientists and engineers is crucial to align on project goals and annotation standards. Staying organized and proactive in seeking feedback can help address ambiguities in training data, while continuous learning about new tools and best practices in machine learning annotation can further enhance overall performance.

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

To thrive as an Assistant LLM Training Specialist, you need a solid understanding of machine learning concepts, data preprocessing, and natural language processing, often supported by a degree in computer science or a related field. Familiarity with Python, deep learning frameworks such as TensorFlow or PyTorch, and experience with data annotation tools are typically required. Strong attention to detail, problem-solving skills, and the ability to collaborate effectively with data scientists and engineers set standout candidates apart. These competencies ensure the accurate preparation and management of data crucial for developing effective large language models.

What are Assistant LLM Training jobs?

Assistant LLM Training jobs typically involve supporting the development, fine-tuning, and evaluation of large language models (LLMs) like GPT or similar AI systems. Individuals in these roles may help gather and curate training data, annotate or review outputs, and assist in testing model performance. They often work closely with machine learning engineers and data scientists to ensure the LLMs produce accurate, ethical, and high-quality responses. These positions may also include monitoring for biases, suggesting improvements, and maintaining documentation related to model training.

What is the difference between Assistant Llm Training vs Data Annotator?

AspectAssistant Llm TrainingData Annotator
Required CredentialsTypically a degree in AI, computer science, or related fieldHigh school diploma or equivalent; training often provided
Work EnvironmentOffice or remote, collaborative with AI teamsMostly remote or on-site, focused on data labeling
Industry UsageAI development, machine learning projectsData preparation for AI and ML models
Common Search & ComparisonOften compared for roles supporting AI trainingCompared for data labeling and annotation tasks

Assistant Llm Training involves preparing and fine-tuning language models, requiring technical skills and relevant degrees. Data Annotator focuses on labeling data to train AI models, often with minimal formal credentials. Both roles support AI development but differ in technical complexity and responsibilities.

More about Assistant Llm Training jobs
What cities are hiring for Assistant Llm Training jobs? Cities with the most Assistant Llm Training job openings:
What are the most commonly searched types of Llm Training jobs? The most popular types of Llm Training jobs are:
What states have the most Assistant Llm Training jobs? States with the most job openings for Assistant Llm Training jobs include:
Machine Learning Systems Engineer, Siri Agent Modeling

Machine Learning Systems Engineer, Siri Agent Modeling

Apple

Cupertino, CA • On-site

Full-time

Posted 9 hours ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

.Join the team redefining what a deeply personal and integrated assistant can be. ..As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS...This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs..
As a Machine Learning Systems Engineer, you will work closely with Siri modeling teams and other cross-functional teams to optimize model training and inference. You will be working across the ML stack at Apple, finding opportunities to make models performant, train quicker, and run faster on Apple's custom Apple Silicon. You will be joining a team that spans data, modeling, evaluation, deployment and working with engineers across ML infrastructure, inference, and framework teams. You will write production-level code to train and deploy models that will impact Apple's customers and enrich their lives. You are an ideal candidate if you: Are not afraid of CUDA OOM or NCCL errors
Experience in model lifecycle of training, evaluation, and deployment of modelsStrong understanding of Machine Learning (ML) model architectures (e.g. Transformers, CNN) and ML training loopStrong proficiency in Python and ML framework such as PyTorchBachelor's degree in Computer Science, Engineering, or related discipline, or equivalent industry/project experienceExperience with agentic AI-assisted coding
Collaborative with experience working in large inter-teams projectsExpertise in ML and LLM optimization such as quantization, KV Cache, Speculative DecodingFamiliarity with ML training methodologies such as FSDP, DDP, and other parallelismExperience in an LLM training/eval library such as HuggingFace transformers, lm evaluation harness, Megatron-LM.Experience in optimizing LLM models and deploying LLM modelsProficiency in a compiled programming language (e.g. Swift, C/C++, Java)

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976