LLM Training Frameworks and Optimization Engineer

Reposted 20 Days Ago
Be an Early Applicant
San Francisco, CA
In-Office
160K-230K
Senior level
Artificial Intelligence • Information Technology
The Role
Develop and optimize distributed training frameworks for large language models, ensuring scalability and performance across training pipelines.
Summary Generated by Built In
About the Role

At Together.ai, we are building cutting-edge infrastructure to enable efficient and scalable training of large language models (LLMs). We focus on optimizing training frameworks, algorithms, and infrastructure to push the boundaries of AI performance, scalability, and cost-efficiency.

We are seeking a LLM Training Frameworks and Optimization Engineer to drive innovations in the development and optimization of distributed training frameworks. In this role, you will ensure that our LLM training pipelines are robust, efficient, and capable of handling the complexities of large-scale distributed systems.

Responsibilities
  • Framework Development and Optimization:
    • Design, implement, and optimize distributed training frameworks tailored for large language models.
    • Develop custom modules, plugins, and features to enhance framework scalability and performance.
  • Algorithmic and Systems Optimization:
    • Optimize communication patterns (e.g., gradient synchronization, all-reduce) in distributed training.
    • Implement techniques like mixed precision, tensor parallelism, pipeline parallelism, and sharded training.
  • Performance Tuning:
    • Conduct in-depth profiling and debugging of training jobs to identify and resolve bottlenecks.
    • Collaborate with hardware teams to optimize performance for GPUs, TPUs, and other accelerators.
  • Scalability and Resilience:
    • Ensure training systems scale efficiently to thousands of nodes and petabytes of data.
    • Develop resilience mechanisms for fault-tolerant and checkpointed training pipelines.
  • Collaboration and Support:
    • Work closely with researchers, data engineers, and platform teams to ensure training frameworks meet model and workload requirements.
    • Provide guidance and tools to improve the overall efficiency of the LLM development lifecycle.
Requirements

Must-Have:

  • Experience:
    • 5+ years of experience in deep learning frameworks, distributed systems, or machine learning infrastructure.
  • Technical Skills:
    • Expertise in distributed training frameworks (e.g., PyTorch DDP, DeepSpeed, Megatron-LM, TensorFlow XLA).
    • Strong understanding of parallelism techniques (e.g., data, tensor, pipeline, and ZeRO-based parallelism).
    • Familiarity with GPU/TPU hardware and deep learning performance optimizations.
  • Programming:
    • Proficient in Python and C++ or CUDA for high-performance computing.
  • Optimization Techniques:
    • Experience with memory optimization techniques (e.g., activation checkpointing, gradient sharding).
    • Knowledge of training dynamics for large-scale LLMs, including hyperparameter tuning and optimization.
  • Soft Skills:
    • Analytical problem-solving skills and a focus on performance improvement.
    • Strong collaboration and communication skills across teams.

Nice-to-Have:

  • Familiarity with graph optimization and compiler-level performance tuning.
  • Contributions to open-source deep learning or distributed training projects.
  • Experience with low-level hardware optimizations (e.g., kernel fusion, custom CUDA kernels).

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  


Top Skills

C++
Cuda
Deepspeed
Megatron-Lm
Python
Pytorch Ddp
Tensorflow Xla
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The Company
San Francisco, California
84 Employees
Year Founded: 2022

What We Do

Together AI is a research-driven artificial intelligence company. We contribute leading open-source research, models, and datasets to advance the frontier of AI. Our decentralized cloud services empower developers and researchers at organizations of all sizes to train, fine-tune, and deploy generative AI models. We believe open and transparent AI systems will drive innovation and create the best outcomes for society

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