MLOps Engineer
BJAK
KubernetesRay
Job Level
Mid-LevelSenior
Tech Stack
PyTorchTensorflow
About the role
- Fine-tune & adapt - Use LoRA/QLoRA to optimize open-source models (LLaMA, Mistral, Gemma)
- Engineer prompts & curates data - Craft prompts and datasets that reflect tone, brand voice, and safety.
- Evaluate models – Build metrics pipelines for perplexity, toxicity, and relevance to ensure safe and high-quality outputs.
- Deploy & monitor – Scale models into production with performance optimization and monitoring for drift.
- Collaborate & deliver – Partner with product, engineering, and design teams to launch user-facing AI features.
Requirements
- Strong experience in transformers, deep learning, and fine-tuning methods (LoRA/QLoRA, SFT, distillation).
- Proficiency with PyTorch (preferred) or TensorFlow.
- Skilled in prompt engineering and dataset curation for alignment with tone, safety, and trust.
- Familiar with evaluation metrics: perplexity, toxicity, relevance.
- Strong software engineering foundations in algorithms, data structures, and clean code practices.