Deploy LLaMA 3.1 8B on Lambda Labs
Budget: $100 – $250 USD
AI Engineer Needed to Deploy LLaMA 3.1 8B on Lambda Labs
Description:
We are looking for an experienced Machine Learning Engineer / DevOps Specialist to set up LLaMA 3.1 8B on a Lambda Labs virtual machine. The setup includes installing dependencies, running inference, and optimizing performance. This is a one-time contract with potential for future collaborations.
Responsibilities:
Provision a Lambda Labs VM with the appropriate GPU configuration
Install necessary dependencies (CUDA, PyTorch, Hugging Face, etc.)
Download and configure LLaMA 3.1 8B model
Set up inference pipeline (PyTorch or vLLM)
Implement basic optimizations (FlashAttention, 8-bit quantization, etc.)
Deliver a working, documented setup that can be replicated
Requirements:
Strong experience with deploying LLaMA, Mistral, or Falcon models
Expertise in Lambda Labs, AWS, or other GPU cloud services
Proficiency in Python, PyTorch, and Hugging Face Transformers
Familiarity with CUDA, cuDNN, and GPU acceleration techniques
Experience with LLM optimizations (quantization, vLLM, FlashAttention, Triton, etc.)
Ability to work independently and deliver quickly (3-6 hours max)
Nice to Have (Bonus Points):
Experience fine-tuning or serving models via FastAPI / OpenAI-style API
Familiarity with low-latency inference techniques
Deliverables:
Fully functional LLaMA 3.1 8B deployment on Lambda Labs
Step-by-step documentation for reproducibility
Performance benchmark results (latency, VRAM usage, etc.)
Budget & Timeline:
Fixed price:
Estimated time: 2-4 hours
Start immediately
If you are an experienced AI engineer ready to deploy this fast, please send a proposal with your past LLM deployment experience and an estimated timeline.
Description:
We are looking for an experienced Machine Learning Engineer / DevOps Specialist to set up LLaMA 3.1 8B on a Lambda Labs virtual machine. The setup includes installing dependencies, running inference, and optimizing performance. This is a one-time contract with potential for future collaborations.
Responsibilities:
Provision a Lambda Labs VM with the appropriate GPU configuration
Install necessary dependencies (CUDA, PyTorch, Hugging Face, etc.)
Download and configure LLaMA 3.1 8B model
Set up inference pipeline (PyTorch or vLLM)
Implement basic optimizations (FlashAttention, 8-bit quantization, etc.)
Deliver a working, documented setup that can be replicated
Requirements:
Strong experience with deploying LLaMA, Mistral, or Falcon models
Expertise in Lambda Labs, AWS, or other GPU cloud services
Proficiency in Python, PyTorch, and Hugging Face Transformers
Familiarity with CUDA, cuDNN, and GPU acceleration techniques
Experience with LLM optimizations (quantization, vLLM, FlashAttention, Triton, etc.)
Ability to work independently and deliver quickly (3-6 hours max)
Nice to Have (Bonus Points):
Experience fine-tuning or serving models via FastAPI / OpenAI-style API
Familiarity with low-latency inference techniques
Deliverables:
Fully functional LLaMA 3.1 8B deployment on Lambda Labs
Step-by-step documentation for reproducibility
Performance benchmark results (latency, VRAM usage, etc.)
Budget & Timeline:
Fixed price:
Estimated time: 2-4 hours
Start immediately
If you are an experienced AI engineer ready to deploy this fast, please send a proposal with your past LLM deployment experience and an estimated timeline.