GenAI/LLM Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GenAI/LLM Engineer in California, offering an ongoing contract with a target start date next month. Key skills include deep learning frameworks, LLM training techniques, and experience with multi-GPU training.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
760
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πŸ—“οΈ - Date discovered
August 29, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Unknown
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
San Francisco Bay Area
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🧠 - Skills detailed
#Compliance #AI (Artificial Intelligence) #Transformers #"ETL (Extract #Transform #Load)" #Hugging Face #Data Pipeline #Deep Learning #Monitoring #PyTorch #TensorFlow #Documentation #Libraries
Role description
Job Title: GenAI Engineer – AI Solutions Development Location: California (Bay Area preferred) Contract Type: Ongoing Start Date: Targeting next month We’re looking for a GenAI Engineer to join a fast-moving team focused on delivering high-impact AI solutions across multiple business units. This role is ideal for someone who thrives in early-stage discovery environments and enjoys shaping technical direction from the ground up. πŸ” What You’ll Do β€’ Fine-tune foundation models using advanced techniques (LoRA, PEFT, QLoRA) β€’ Build reusable prompt libraries and systematic prompt engineering frameworks β€’ Design and implement retrieval-augmented generation (RAG) pipelines β€’ Optimize model performance using quantization, pruning, and hybrid memory strategies β€’ Develop advanced prompting strategies (e.g., chain-of-thought, agent orchestration) β€’ Collaborate with MLOps to deploy, monitor, and retrain models β€’ Establish prompt versioning and governance systems 🧠 What You Bring β€’ Strong experience with deep learning frameworks (PyTorch, TensorFlow) and Hugging Face Transformers β€’ Familiarity with DSPy and LLM training techniques β€’ Hands-on knowledge of multi-GPU training, memory optimization, and parallelization β€’ Understanding of LLMOps workflows and production monitoring β€’ Ability to interpret research and apply emerging techniques β€’ Experience building data pipelines for domain-specific model adaptation πŸ’‘ Bonus Skills β€’ Experience with agent-based architectures and conversation orchestration β€’ Background in technical documentation, regulatory compliance, or utility operations (a plus, not required)