This is your chance to contribute to an end-to-end AI ecosystem; designing, deploying, and scaling intelligent systems that drive real business impact. Youll work alongside talented Engineers, Data Scientists, and business leaders to turn ideas into intelligent, production-ready solutions. Why This Role?: Be part of an AI-first transformation , building capability from scratch Exposure to full AI stack development (ML, data, infrastructure, and applications) Structured career pathways and mentorship from senior experts Hybrid work model with flexibility and strong peer collaboration Continuous learning through training, certifications, and AI research exploration Key Responsibilities: AI Solution Development & Deployment: Build, train, and deploy ML/DL models for NLP, computer vision, time series, and generative AI. Implement prompt engineering, RAG architecture, and agent-based systems. Data Engineering & Pipeline Management: Design and maintain ETL/ELT data pipelines. Work with SQL/NoSQL and vector databases. Ensure high data quality and readiness for ML models. AI Operations & Infrastructure: Deploy models to production with CI/CD pipelines, containerization (Docker, Kubernetes), and monitoring frameworks. Manage model versioning, retraining, and drift detection. Platform & Cloud Engineering: Develop AI platform tools and infrastructure using Infrastructure-as-Code and cloud deployment (AWS/Azure/GCP). Business Collaboration: Translate business needs into technical AI solutions. Ensure responsible AI practices and ethical model implementation. Research & Continuous Learning: Stay current with the latest AI advancements. Experiment, evaluate, and share findings with peers. Job Experience and Skills Required : Education Bachelors or Honours Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or Information Systems (completed within the last 18 months or graduating in 2025). Experience Early-career or graduate-level experience (internship, academic project, or self-directed learning in AI/ML). Skills: Strong Python programming skills (Java, JavaScript, or Go advantageous). Good understanding of data structures, algorithms, and database concepts . Familiarity with Git , SQL , and cloud computing platforms (AWS, Azure, or GCP). Basic understanding of machine learning concepts and frameworks. Advantageous Qualifications & Experience: Masters Degree or Postgraduate AI/ML coursework. Exposure to ML frameworks (TensorFlow, PyTorch, or scikit-learn). Experience with APIs, Docker/Kubernetes, Terraform, or MLOps tools. Demonstrated AI/ML projects on GitHub, Kaggle, or open-source contributions Apply now!

Key Responsibilities: AI Solution Development & Deployment: Design, train, and fine-tune machine learning and deep learning models (NLP, computer vision, time series, and generative AI). Build and deploy AI applications using LLMs and ML frameworks. Implement prompt engineering, retrieval-augmented generation (RAG), and agent-based systems. Create APIs, integrations, and production-ready Python code for scalable AI services. Data Engineering & Pipeline Management: Gather, clean, and transform raw data into machine-learning-ready formats. Build and manage ETL/ELT pipelines using SQL, NoSQL, and vector databases. Develop and optimise data warehouses and real-time data processing workflows. Ensure data quality, governance, and observability. AI Operations & Infrastructure: Deploy and monitor ML models in production environments. Build CI/CD pipelines for AI model deployment. Work with containerisation and orchestration tools (Docker and Kubernetes). Manage cloud resources, model versioning, and retraining cycles. Platform Engineering: Develop internal AI tools and platform infrastructure. Apply infrastructure-as-code and workflow orchestration techniques. Work with microservices and API gateway patterns. Business Collaboration: Collaborate with product, engineering, and business teams to identify and deliver AI solutions. Translate business challenges into data-driven, ethical, and explainable AI systems. Identify automation opportunities and evaluate business value. Research & Continuous Learning: Stay current with emerging AI technologies and frameworks. Experiment with new architectures and share learnings with the wider team. Job Experience and Skills Required: Education: Bachelors or Honours Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Information Systems, or a related field. Graduated within the last 18 months or graduating in 2025. Strong academic record. Technical Skills: Proficient in Python or similar programming languages (Java, JavaScript, and Go). Strong understanding of data structures, algorithms, and software design principles. Proficient in SQL and database concepts. Understanding of ML fundamentals, statistics, and probability. Familiarity with Git, cloud platforms (AWS, Azure, or GCP), and modern ML frameworks. Apply now!