Role: GenAI Ops Engineer

Location: Austin, TX (Onsite day 1)

Type: Contract

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 GCP.
• 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.