AI​/ML Engineer

We are a leading provider of reverse logistics and returns management solutions, leveraging technology to optimize supply chains and maximize value recovery. We are expanding our AI/ML capabilities to include generative AI-driven solutions, RAG applications, and predictive models for retail pricing using collected data from multiple sources.

• 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 (data engineering, operations, and business) to define AI/ML use cases and deliver solutions.
• Monitor and improve model performance, ensuring robustness, scalability, and reliability.
• Utilize tools like OpenAI API, Hugging Face, Lang Chain, Llama Index, and cloud platforms (AWS, Azure, GCP) for AI development and deployment.

• 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 Tensor Flow, PyTorch, and Scikit-Learn.
• Hands‑on experience with LLMs, NLP models, prompt engineering, and tools like OpenAI API, Hugging Face Transformers, Lang Chain, Llama Index, 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 Sage Maker, GCP Vertex AI, or Azure ML).
• Knowledge of MLOps best practices, including CI/CD pipelines, version control, and model monitoring.
• Excellent problem‑solving skills and ability to communicate complex AI concepts clearly.

• 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.

Mid‑Senior level

Full‑time

Engineering and Information Technology

Technology, Information and Internet

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