AI/ML Engineer (AI Engineering)

TL;DR

AI/ML Engineer (AI Engineering): Developing pricing models for retail products and enhancing operational efficiency through AI automation with an accent on generative AI-driven solutions, RAG applications, and predictive models. Focus on applying cutting-edge techniques in LLMs, NLP, and agentic AI frameworks.

Company

hirify.global is a leading provider of reverse logistics and returns management solutions, leveraging technology to optimize supply chains and maximize value recovery.

What you will do

• Design, build, and deploy predictive models for retail pricing using data from various internal and external sources.
• Develop and fine-tune generative AI models (LLMs) for automation, data augmentation, and content generation.
• Implement RAG (Retrieval-Augmented Generation) applications to enhance AI systems with dynamic information retrieval.
• Build and integrate AI agentic frameworks for autonomous decision-making and task automation.
• Build and maintain scalable machine learning pipelines for data processing, training, and inference.
• Collaborate with cross-functional teams to define AI/ML use cases and deliver solutions.

Requirements

• 5+ years of experience in AI/ML engineering with a strong focus on generative AI, RAG applications, and predictive modeling.
• Proficiency in Python and AI/ML libraries like TensorFlow, PyTorch, and Scikit-Learn.
• Hands-on experience with LLMs, NLP models, prompt engineering, and tools like OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, and AI agentic frameworks.
• Strong understanding of data preprocessing, feature engineering, and model selection for time series and pricing data.
• Experience in building and deploying ML models on cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
• Knowledge of MLOps best practices, including CI/CD pipelines, version control, and model monitoring.

Nice to have

• Experience with AI-driven pricing optimization in retail, logistics, or e-commerce.
• Experience developing and deploying RAG systems for dynamic content retrieval.
• Familiarity with AI agentic frameworks for building autonomous AI agents.
• Prior work in AI automation for supply chain, demand forecasting, or pricing strategies.
• Strong knowledge of AI/ML ethics, ensuring fairness and bias mitigation in models.

Culture & Benefits

• Leveraging technology to optimize supply chains and maximize value recovery.
• Expanding AI/ML capabilities to include generative AI-driven solutions.