Seattle, WA · On-site
Preferred : • 5+ years of LLM training in a production environment • Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. • Publications in top ...
Seattle, WA · On-site
Preferred : • 5+ years of LLM training in a production environment • Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. • Publications in top ...
Seattle, WA · On-site
$139K - $183K/yr
The role involves working on distributed Deep Learning, particularly within LLM training and inference stacks. A strong passion for collective communication and networking is desirable. The candidate ...
Seattle, WA · On-site
$139K - $183K/yr
The role involves working on distributed Deep Learning, particularly within LLM training and inference stacks. A strong passion for collective communication and networking is desirable. The candidate ...
... LLM ... training and inference. * Conducting regular technical customer meetings for project/product ...
... LLM ... training and inference. * Conducting regular technical customer meetings for project/product ...
Required : • Strong excitement about system optimization • Experience with multi-node LLM training and inference • Experience with developing large-scale distributed ML systems • Strong ...
Required : • Strong excitement about system optimization • Experience with multi-node LLM training and inference • Experience with developing large-scale distributed ML systems • Strong ...
Required : • Strong excitement about system optimization • Experience with multi-node LLM training and inference • Experience with developing large-scale distributed ML systems • Strong ...
Required : • Strong excitement about system optimization • Experience with multi-node LLM training and inference • Experience with developing large-scale distributed ML systems • Strong ...
Required : • Strong excitement about system optimization • Experience with multi-node LLM training and inference • Experience with developing large-scale distributed ML systems • Strong ...
Required : • Strong excitement about system optimization • Experience with multi-node LLM training and inference • Experience with developing large-scale distributed ML systems • Strong ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Strong publication record in IEEE or equivalent journals/conferences related to LLM training, data preparation, or synthetic data generation. Proficiency in deep learning frameworks such as ...
Strong publication record in IEEE or equivalent journals/conferences related to LLM training, data preparation, or synthetic data generation. Proficiency in deep learning frameworks such as ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Responsibilities : • Identify and maintain LLM training and serving benchmarks, using them to identify performance opportunities, drive XLA:GPU/Triton performance toward XLA releases. • Engage ...
Responsibilities : • Identify and maintain LLM training and serving benchmarks, using them to identify performance opportunities, drive XLA:GPU/Triton performance toward XLA releases. • Engage ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Improve the efficiency of LLM, VLM, and agent training and evaluation pipelines, including distributed training, inference serving, data loading, checkpointing, memory usage, and GPU utilization.
Improve the efficiency of LLM, VLM, and agent training and evaluation pipelines, including distributed training, inference serving, data loading, checkpointing, memory usage, and GPU utilization.
Seattle, WA · On-site
$122K - $160K/yr
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
Seattle, WA · On-site
$122K - $160K/yr
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
Seattle, WA · On-site
$111K - $151K/yr
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Seattle, WA · On-site
$111K - $151K/yr
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Seattle, WA · On-site
$111K - $151K/yr
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Seattle, WA · On-site
$111K - $151K/yr
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Seattle, WA · On-site
$111K - $151K/yr
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
Seattle, WA · On-site
$111K - $151K/yr
... LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine ...
$35.8K - $43.9K
15% of jobs
$43.9K - $52K
7% of jobs
$54.5K is the 25th percentile. Wages below this are outliers.
$52K - $60.2K
10% of jobs
$60.2K - $68.3K
11% of jobs
The median wage is $70.6K / yr.
$68.3K - $76.4K
22% of jobs
$76.4K - $84.6K
4% of jobs
$90.4K is the 75th percentile. Wages above this are outliers.
$84.6K - $92.7K
7% of jobs
$92.7K - $100.8K
7% of jobs
$100.8K - $108.9K
4% of jobs
$108.9K - $117.1K
5% of jobs
$117.1K - $125.2K
6% of jobs
$35.8K
$76.8K
$125.2K
To excel in LLM Training, you need a strong background in machine learning, natural language processing (NLP), and computer science, often backed by an advanced degree in a related field. Experience with programming languages such as Python, frameworks like PyTorch or TensorFlow, and familiarity with data annotation tools are essential, along with knowledge of cloud platforms and distributed computing. Strong analytical thinking, effective communication, and the ability to collaborate across interdisciplinary teams set top candidates apart. These skills ensure high-quality model development, efficient project execution, and the ability to adapt to evolving AI technologies.
Professionals specializing in LLM Training often work closely with data engineers, software developers, domain experts, product managers, and quality assurance analysts. Collaboration is essential for collecting and preprocessing training data, integrating models into products, and ensuring outputs meet business and user requirements. These roles frequently participate in agile project workflows, contribute to cross-functional team meetings, and collaborate on continuous model improvements. Engaging with diverse teams expands your understanding of product goals and helps you deliver robust and reliable language models that align with organizational objectives.
An LLM Training job involves developing, fine-tuning, and optimizing large language models (LLMs) to improve their performance and accuracy. This role typically includes data collection, preprocessing, model training, evaluation, and troubleshooting issues related to bias, efficiency, and scalability. Professionals in this field work with machine learning frameworks, large datasets, and computational resources to enhance AI capabilities. They may also collaborate with researchers, engineers, and product teams to deploy models for real-world applications.
Seattle, WA • On-site
Full-time
Posted 8 days ago
Sourced by ZipRecruiter
Software development
201 - 500 Employees
San Francisco, CA, US
2016
