Applied AI/ML Engineer

Responsibilities:

• • Turn ambiguous product problems into working AI systems in production
  • Evaluate and choose the right approach: embeddings, RAG, fine-tuning, or classical ML
  • Build end-to-end pipelines [Data ingestion → cleaning → feature engineering, Model development → evaluation → deployment]
  • Develop core capabilities like Semantic search, Product recommendations & intelligent substitutions
  • Cost prediction and optimization models
  • Partner closely with product and engineering to ship fast and iterate based on real usage
  • Continuously improve models using feedback loops and performance monitoring

Required Skills / Qualifications:

• • 5 – 8 years of experience in applied AI/ML
  • Strong Python skills and hands-on experience with ML frameworks (PyTorch, TensorFlow, or similar)
  • Experience working with [LLMs (fine-tuning, RAG, prompt design), Embeddings and vector search]
  • Ability to make practical decisions on:
  • Model selection [Accuracy vs latency vs cost trade-offs, Experience deploying models into production environments]
  • Comfortable working with messy, real-world data
    • Familiarity with tools like LangChain, LlamaIndex, Pinecone, or Weaviate