Matific is a rapidly growing start-up company, making cool education products used in thousands of schools around the world. Matific is on a mission to empower teachers and give children all over the world access to state-of-the-art mathematics and science education. By combining great minds and creative souls, we make learning child's play.

Matific

Machine Learning Engineer

Customer Support Specialist

Principal Data Engineer

Matific is seeking a Machine Learning Engineer to join their global EdTech team. This role involves end-to-end ownership of the ML lifecycle, from model design and development to scalable deployment and monitoring in production. The engineer will focus on developing high-impact ML solutions, ensuring reliability and performance, and bringing state-of-the-art models from concept to production, combining deep ML research with strong engineering and MLOps practices.

<h3 class="text-xl md:text-2xl font-bold mt-8 mb-3 text-gray-800">Description</h3>ABOUT MATIFICMatific is a leading global EdTech provider, delivering an adaptive online learning platform for primary school mathematics. With our product being utilised by millions of students, teachers and parents in 100+ countries we are helping educate the youth and bring equality to education. With over $50M USD invested and a global team of over 200+ employees, we are committed to achieving our goals. We’ve also picked up a number of awards including numerous CODiEs, Academics’ Choice and Edtech Digest to name a few.THE ROLEWe are seeking a skilled Machine Learning Engineer to join our team. This role involves end-to-end ownership of the machine learning lifecycle — from model design and development to scalable deployment and monitoring in production. You will play a key role in developing high-impact ML solutions and ensuring their reliability and performance on our platform. This role combines deep ML research with strong engineering and MLOps practices to bring state-of-the-art models from concept to production.KEY RESPONSIBILITIES<ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Design, develop, and train robust machine learning models, with a focus on transformer-based architectures, large language models (LLMs), and multimodal systems.</li><li class="leading-relaxed">Conduct applied research and experimentation in cutting-edge areas such as agentic AI, few-shot learning, tool-use capabilities and prompt engineering.</li><li class="leading-relaxed">Conduct data exploration, feature engineering, and experimentation to optimize model performance, leveraging SQL for large-scale data analysis and extraction.</li><li class="leading-relaxed">Lead cloud-based deployment and operationalization of ML models, primarily on AWS.</li><li class="leading-relaxed">Build and maintain automated CI/CD pipelines tailored for ML workflows, including data validation, model versioning, testing, and rollout.</li><li class="leading-relaxed">Monitor model performance in production, implement retraining strategies, and manage model drift.</li><li class="leading-relaxed">Scale ML pipelines and inference systems to handle large datasets and high-throughput environments efficiently.</li><li class="leading-relaxed">Collaborate closely with data scientists, software engineers, and product teams to integrate ML solutions into customer-facing products and internal systems.</li><li class="leading-relaxed">Drive best practices in ML system design, model reproducibility, and responsible AI.</li><li class="leading-relaxed">Stay current with emerging trends, tools, and techniques in machine learning, deep learning, and MLOps.</li></ul><h3 class="text-xl md:text-2xl font-bold mt-8 mb-3 text-gray-800">Requirements</h3><ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Bachelor's degree in Computer Science, Data Science, or a related field. Advanced degrees preferred.</li><li class="leading-relaxed">Minimum of 3 years of hands-on experience in machine learning, with a demonstrable portfolio of projects.</li><li class="leading-relaxed">Deep Learning: Familiarity with neural network architectures, including CNNs, RNNs, and Transformers.</li><li class="leading-relaxed">Proficiency in SQL and data analytics—able to query, transform, and analyze large datasets to support modelling and decision-making.</li><li class="leading-relaxed">Experience working with platforms such as Kubeflow in managing ML experiments is an added benefit.</li><li class="leading-relaxed">Strong skills in evaluating, fine-tuning, and scaling ML models in real-world production settings.</li><li class="leading-relaxed">Proficient in ML frameworks and languages such as TensorFlow, PyTorch, and Python.</li><li class="leading-relaxed">Exceptional problem-solving skills, analytical mindset, and attention to detail.</li><li class="leading-relaxed">Excellent communication skills, both verbal and written.</li></ul>

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Machine Learning Engineer

Customer Support Specialist

Principal Data Engineer

Job Details