AI/ML Engineer at LawPavilion Business Solutions

About the Role:

• Are you passionate about artificial intelligence and machine learning, and how they can transform real-world industries? We are building next-generation legal technology solutions that are redefining how legal services are delivered across Africa. As an AI/ML Engineer, you will design, develop, and deploy intelligent solutions across our legal tech products. You will work closely with software engineers, product managers, and legal professionals to translate complex legal processes and data into scalable, AI-driven

Key Responsibilities:

• Design, train, and optimize machine learning models for NLP tasks such as information extraction, document classification, legal search, and text analysis.
• Collaborate with product and engineering teams to integrate AI solutions into production systems.
• Perform data preprocessing, annotation, and feature engineering on legal and text-based datasets.
• Research, evaluate, and implement state-of-the-art AI and ML models aligned with product needs.
• Monitor, maintain, and continuously improve the performance and scalability of deployed models,
• Ensure model interpretability, explainability, and ethical AI compliance.
• Support the development of data pipelines and internal tools for AI development and deployment.

Qualifications and Skills:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Minimum of 2 years’ hands-on experience in AI/ML engineering, with strong exposure to NLP and transformer-based models.
• Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Experience with NLP tools and frameworks, including spaCy, NLTK, Hugging Face Transformers, and OpenAI libraries.
• Proven experience building and deploying Generative AI solutions, including text generation, summarisation, and conversational agents.
• Practical experience implementing Retrieval-Augmented Generation (RAG) pipelines using LLMs and vector databases.
• Experience deploying models via REST APIs, Docker containers, and cloud platforms such as AWS, GCP, or Azure.
• Solid understanding of data structures, algorithms, and core software engineering principles.
• Experience with vector databases such as Pinecone, Milvus, or similar platforms.
• Experience working with large-scale text-based or legal datasets is an added advantage.
• Strong analytical, problem-solving, and collaboration skills.