Develop scalable and efficient AI pipelines for training, testing and deploying machine learning models in a production environment.
Optimize performance and accuracy of AI models through experimentation and fine-tuning.
Thorough understanding of the Machine Learning Operation (MLOps) and model lifecycle
Stay up to date with the latest advancements in AI and machine learning technologies and incorporate into our solutions as appropriate.
Interact with stakeholders and program management to understand client requirements
Solution Design – Using predefined architectural components to agree an acceptable design
Deliver software development for clients, whilst collaborating with team members at various levels across the globe
Requirements & Skills:
Degree in Computer Science, Machine Learning, or a related field.
Experience with big data technologies (e.g., Hadoop, Spark) and distributed computing frameworks.
Knowledge of software engineering best practices, including version control, automated testing, and continuous integration/continuous deployment (CI/CD).
Experience with natural language processing (NLP), computer vision, or other specialized domains within AI/ML.
Proven experience in developing AI/ML solutions, preferably in a commercial setting.
Strong proficiency in Python programming and popular libraries/frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Solid understanding of machine learning concepts, algorithms, and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc.
Hands-on experience with data preprocessing, feature engineering, and model evaluation/validation.
Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models at scale.
Excellent problem-solving skills, attention to detail, and ability to work independently or collaboratively in a team environment.
Effective communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
