Oved GroupRemote
AI Application Engineer (Full Stack)
United States of America
Full Time
10 hours ago
Visa Sponsor
Key skills
PythonSQLAIMachine LearningMLComputer VisionLLMOpenAIAnthropicRAGLangChainLlamaIndexPyTorchTensorFlowscikit-learnXGBoostMLflowChromaPineconeFastAPIFlaskAWSAzureGCPDockerREST APIGitVersion Control
About this role
Oved Group is an industry leader in global fashion and apparel design with over 40 years of success. They are seeking an AI Application Engineer (Full Stack) to explore and implement AI and machine learning solutions across various business functions, including demand forecasting and personalization initiatives.
Responsibilities:
- Explore where machine learning and AI can create the most impact across the business, then help translate those opportunities into practical use cases and prototypes
- Build and iterate on demand forecasting and inventory planning models that help reduce overproduction and stockouts
- Support personalization and recommendation initiatives across the e-commerce experience
- Develop or integrate LLM-powered tools for internal workflows, including product copy, search, customer support automation, and operational productivity
- Contribute to computer vision and visual search opportunities tied to product imagery, fit, and customer experience
- Help design AI agents and workflow automations that streamline repetitive processes across the organization
- Create and maintain data pipelines and foundational infrastructure needed to support ML / AI experimentation and deployment
- Partner cross-functionally to test ideas quickly, evaluate outcomes, and refine solutions based on business value
Requirements:
- Bachelor's degree in computer science, data science, mathematics, or a related technical field, or equivalent practical experience
- 1–3 years of professional or research experience in ML, AI engineering, or data science; coursework, bootcamp work, and independent projects may be considered alongside professional experience
- Strong Python and SQL skills
- Experience with traditional ML approaches such as scikit-learn and XGBoost
- Hands-on experience with model training, evaluation, and tuning
- Working knowledge of at least one cloud platform (Azure, AWS, or GCP)
- Git / version control proficiency
- Strong grounding in statistics and probability fundamentals
- LLM integration experience using platforms such as OpenAI or Anthropic
- RAG pipelines and familiarity with LangChain or LlamaIndex
- Vector databases such as Pinecone, FAISS, or Chroma
- AI agents and tool use
- PyTorch or TensorFlow
- REST API development using FastAPI or Flask
- Docker and experiment tracking tools such as MLflow or Weights & Biases