How you’ll contribute

• Design, implement, and deploy machine learning models, deep learning models, and AI-driven features within our SaaS platform.
• Work with large datasets, clean and preprocess data, and perform exploratory data analysis(EDA) to identify patterns and insights.
• Develop and select meaningful features for predictive models, ensuring high accuracy and efficiency.
• Partner with product managers, software engineers, and data scientists to ensure AI models meet business requirements and align with product roadmaps.
• Optimise models for performance, scalability, and real-time use cases in a production environment.
• Monitor and update models post-deployment, ensuring they continue to deliver high-quality results, and fine-tune based on real-time data.
• Stay current with the latest AI research and advancements in machine learning and AI technologies. Propose and implement new algorithms, architectures, and tools.
• Maintain clear documentation for AI models, systems, and processes to ensure transparency and knowledge sharing within the team.

Who you are

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience in AI/ML engineering or related fields, ideally within a SaaS or cloud-based environment.
• Proven experience with machine learning frameworks such as TensorFlow, PyT orch, Scikit-learn, or Keras.
• Strong proficiency in Python (other languages such as R, Java, or C++ are a plus).
• Experience with cloud services like AWS, Azure, or Google Cloud Platform (GCP) for model deployment and scaling.
• Solid understanding of data structures, algorithms, and software engineering best practices.
• Expertise in model development, training, and evaluation (classification, regression, clustering, NLP).
• Strong background in data preprocessing, feature engineering, and time-series analysis.
• Experience with version control (Git) and agile development methodologies.
• Familiarity with MLOps practices, model versioning, and CI/CD pipelines for AI applications.
• Excellent problem-solving and debugging skills.
• Strong communication and teamwork skills, with the ability to explain complex technical concepts to non-technical stakeholders.