AIML Engineer

AIML Engineer QubeAxis Stockton, CA Job Details Full-time $81,880.39 - $98,608.64 a year 17 hours ago Qualifications AI models Containerization systems Computer Science Software coding Public Cloud AI platforms (beyond public GPTs) Computational framework Prompt engineering Bachelor's degree Model deployment Version control systems Continuous integration Supervised learning Natural language processing Software documentation DevOps automation Unsupervised learning Machine learning libraries Model evaluation Machine learning frameworks MLOps Providing code feedback Full Job Description Required Skills & Qualifications Python proficiency Must Have — production-quality code, OOP, async programming, and familiarity with testing frameworks (pytest). Machine learning fundamentals Must Have — solid grasp of supervised/unsupervised learning, model evaluation, bias-variance tradeoff, and regularisation.

LLM & NLP

experience Must Have — hands-on work with transformer architectures, prompt engineering, fine-tuning (LoRA / QLoRA), and tokenisation. RAG pipeline development Must Have — experience building retrieval-augmented systems with vector databases (Pinecone, Weaviate, or pgvector). LLM frameworks Must Have — practical knowledge of LangChain, LlamaIndex, or equivalent orchestration tools. Cloud & MLOps basics Must Have — experience with at least one major cloud (AWS / GCP / Azure), containerisation (Docker), and CI/CD for ML workflows. Version control & collaboration Must Have — Git, code review culture, and documentation practices. Preferred Qualifications B.Tech / B.S. / M.S. in Computer Science, Data Science, Mathematics, or a related field — or equivalent industry experience. Nice to Have Experience with PyTorch or TensorFlow for custom model training and fine-tuning on domain datasets. Nice to Have Familiarity with Hugging Face ecosystem — Transformers, PEFT, Datasets, Evaluate libraries. Nice to Have Exposure to multi-modal models (vision-language, speech, or document understanding). Nice to Have Knowledge of model serving frameworks — TorchServe, BentoML, vLLM, or Triton Inference Server. Nice to Have Published work, open-source contributions, Kaggle Top placements, or demonstrable personal AI projects on GitHub. Nice to Have Understanding of data privacy, responsible AI principles, and model interpretability (SHAP, LIME). Nice to

Have Pay:

$81,880.39 - $98,608.64 per year

Work Location:

Hybrid remote in Stockton, CA 95210