What are the responsibilities and job description for the GenAI Ops Engineer-Onsite position at BURGEON IT SERVICES LLC?
Job Details
Role: GenAI Ops Engineer
Location: Austin, TX
Onsite
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Mandatory Skills:
GenAI Models, operations, Mlops, Train and fine-tune LLMs using PyTorch, DeepSpeed, and LoRA, RAG, ML flow, Python, Transformer Architecture
Job Description:
We are looking for a GenAI Ops Engineer to train, fine-tune, and deploy Generative AI models (LLMs, Diffusion Models, Transformers, etc.). You will optimize model performance, manage training pipelines, and integrate AI solutions into production.
Key Responsibilities:
- Train and fine-tune LLMs using PyTorch, DeepSpeed, and LoRA.
- Optimize inference using ONNX, vLLM, TensorRT, and GPU acceleration.
- Manage datasets, preprocess data, and implement RAG with vector databases (FAISS, Chroma, Pinecone).
- Automate training workflows using ML flow, Weights & Biases, and Ray.
- Deploy models using Kubernetes, Docker, and cloud AI services AWS or Google Cloud Platform.
- Monitor model performance, mitigate drift, and optimize resource utilization.
Requirements:
- Experience with LLM training, fine-tuning, and inference optimization.
- Proficiency in Python, cloud AI services, and distributed training.
- Familiarity with retrieval-augmented generation (RAG) and prompt engineering.
- Strong problem-solving skills and ability to work in fast-paced AI environments.
Preferred:
- Experience with open-weight models (LLaMA, Mistral, Gemma, Falcon, etc.).
- Hands-on knowledge of multi-agent architectures and synthetic data generation.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
