We are seeking a skilled and motivated Artificial Intelligence Engineer to contribute to the development and deployment of AI solutions across the organization. This mid-level role focuses on building and optimizing models in Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLMs), supporting innovation and operational efficiency. 

The ideal candidate combines strong technical expertise with a collaborative mindset, working closely with senior engineers, data scientists, and business stakeholders to deliver scalable, high-impact AI systems. This is a remote position offering opportunities for growth, mentorship, and exposure to cutting-edge AI technologies. 

• Contribute to the design, development, and deployment of ML, NLP, and LLM models for real-world applications. 
• Collaborate with cross-functional teams to integrate AI models into production systems and workflows. 
• Assist in building end-to-end AI pipelines, including data ingestion, preprocessing, model training, and evaluation. 
• Support the implementation of Retrieval-Augmented Generation (RAG) and other GenAI techniques. 
• Monitor and improve model performance, scalability, and reliability. 
• Stay informed on emerging AI technologies and research to enhance solution quality.
• Participate in code reviews, documentation, and knowledge sharing within the team.
• Uphold ethical AI practices and contribute to discussions on fairness, transparency, and data privacy. 
• Communicate effectively with technical and non-technical stakeholders to align on project goals. 
• Receive mentorship from senior engineers and contribute to a culture of learning and innovation. 

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field. 
• 2–5 years of experience in AI/ML development, with hands-on exposure to NLP and LLMs.
• Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face). 
• Experience with data preprocessing, model training, and deployment in cloud environments. 
• Familiarity with REST APIs, containerization (Docker), and version control (Git). 
• Understanding of ethical AI principles and data privacy considerations. 
• Strong problem-solving skills and ability to work independently and in teams. 
• Excellent communication and documentation abilities. 
• Experience with GenAI, RAG, or transformer-based architectures. 
• Exposure to MLOps tools and CI/CD pipelines. 
• Familiarity with stream processing and real-time data systems. 
• Knowledge of regulatory standards in AI (e.g., GDPR, HIPAA compliance).
• Professional experience with at least one of the following: 
• Transformers 
• Generative AI 
• Deep Learning 
• Machine Learning Ops