AIML Engineer

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