AI Engineer

Job not on LinkedIn

🕒 December 16, 2025

🗽 New York – Remote

🗽 New York – Remote

💵 $60k - $180k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 AI Engineer

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BoxNCase

WebsiteLinkedInAll Job Openings

51 - 200 employees

🛍️ eCommerce

🤝 B2B

🛒 Retail

eCommerce • B2B • Retail

BoxNCase is a specialty food and grocery wholesale platform that allows customers to purchase directly from a wide selection of premium products without any membership fees or minimum orders. With over 30,000 items available for bulk buying, BoxNCase caters to both retailers and individual consumers, making it easy to access gourmet and fine foods, condiments, snacks, beverages, and more. The company prides itself on being one of the largest direct importers and wholesalers in the sector, offering convenience and savings on high-quality culinary offerings.

📋 Description

• Develop AI Models: Design and implement machine learning models and algorithms to solve specific business challenges. • Build GenAI Applications: Architect applications using LLMs (OpenAI, Llama 2, Anthropic) and RAG (Retrieval-Augmented Generation) pipelines. • Fine-Tuning: Fine-tune pre-trained models on proprietary datasets to improve performance and domain accuracy. • Model Deployment: Deploy and scale AI models into production environments using MLOps best practices (Docker, Kubernetes). • Data Engineering: Collaborate with data teams to clean, preprocess, and manage large datasets for model training. • Stay Cutting-Edge: Continuously research and integrate the latest advancements in AI/ML (e.g., Agents, Vector Databases) into our product stack.

🎯 Requirements

• 2+ years of experience in Data Science, Machine Learning Engineering, or AI Research. • Expert-level proficiency in Python and familiarity with libraries like Pandas, NumPy, and Scikit-learn. • Strong experience with frameworks such as PyTorch, TensorFlow, or Keras. • Solid understanding of Natural Language Processing techniques, Transformers, and Embeddings. • Experience working with APIs (REST/GraphQL) and integrating third-party AI services (OpenAI, Hugging Face). • Familiarity with deploying models on AWS (SageMaker), Google Cloud (Vertex AI), or Azure.

🏖️ Benefits

• Remote Flexibility: Work from anywhere in the world or hybrid options. • Equity: Stock options available for early hires. • Tech Budget: Annual stipend for hardware and AI research tools.