Machine Learning Engineer

33 Minutes ago • 3 Years +

Research Development

Job Description

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.

Good To Have:

Experience working with platforms such as Kubeflow in managing ML experiments.

Must Have:

Design, develop, and train robust machine learning models, focusing on transformer-based architectures, LLMs, and multimodal systems.
Conduct applied research and experimentation in agentic AI, few-shot learning, tool-use capabilities, and prompt engineering.
Perform data exploration, feature engineering, and experimentation to optimize model performance, leveraging SQL.
Lead cloud-based deployment and operationalization of ML models, primarily on AWS.
Build and maintain automated CI/CD pipelines tailored for ML workflows.
Monitor model performance in production, implement retraining strategies, and manage model drift.
Scale ML pipelines and inference systems to handle large datasets and high-throughput environments.
Collaborate closely with data scientists, software engineers, and product teams to integrate ML solutions.
Drive best practices in ML system design, model reproducibility, and responsible AI.
Stay current with emerging trends, tools, and techniques in machine learning, deep learning, and MLOps.
Minimum of 3 years of hands-on experience in machine learning.
Familiarity with neural network architectures, including CNNs, RNNs, and Transformers.
Proficiency in SQL and data analytics.
Strong skills in evaluating, fine-tuning, and scaling ML models in real-world production settings.
Proficient in ML frameworks and languages such as TensorFlow, PyTorch, and Python.

Perks:

A business with a strong purpose: to provide quality education to children everywhere
A fast and exciting scale-up environment
Work in the booming Edtech industry
Collaborate closely with seasoned, successful entrepreneurs from around the world
Opportunity to innovate and challenge the status quo
Great remuneration, paid in USD
A fun-loving office environment with full facilities for tech professionals at One Galle Face Office Tower
Comprehensive insurance coverage for you and your family
Flexibility to support a healthy work-life balance
Access to continuous learning opportunities to enhance your skills and grow your career

Add these skills to join the top 1% applicants for this job

team-management

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aws

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pytorch

deep-learning

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python

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tensorflow

system-design

machine-learning

Description

ABOUT MATIFIC

Matific 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 ROLE

We 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

Design, develop, and train robust machine learning models, with a focus on transformer-based architectures, large language models (LLMs), and multimodal systems.
Conduct applied research and experimentation in cutting-edge areas such as agentic AI, few-shot learning, tool-use capabilities and prompt engineering.
Conduct data exploration, feature engineering, and experimentation to optimize model performance, leveraging SQL for large-scale data analysis and extraction.
Lead cloud-based deployment and operationalization of ML models, primarily on AWS.
Build and maintain automated CI/CD pipelines tailored for ML workflows, including data validation, model versioning, testing, and rollout.
Monitor model performance in production, implement retraining strategies, and manage model drift.
Scale ML pipelines and inference systems to handle large datasets and high-throughput environments efficiently.
Collaborate closely with data scientists, software engineers, and product teams to integrate ML solutions into customer-facing products and internal systems.
Drive best practices in ML system design, model reproducibility, and responsible AI.
Stay current with emerging trends, tools, and techniques in machine learning, deep learning, and MLOps.

Requirements

Bachelor's degree in Computer Science, Data Science, or a related field. Advanced degrees preferred.
Minimum of 3 years of hands-on experience in machine learning, with a demonstrable portfolio of projects.
Deep Learning: Familiarity with neural network architectures, including CNNs, RNNs, and Transformers.
Proficiency in SQL and data analytics—able to query, transform, and analyze large datasets to support modelling and decision-making.
Experience working with platforms such as Kubeflow in managing ML experiments is an added benefit.
Strong skills in evaluating, fine-tuning, and scaling ML models in real-world production settings.
Proficient in ML frameworks and languages such as TensorFlow, PyTorch, and Python.
Exceptional problem-solving skills, analytical mindset, and attention to detail.
Excellent communication skills, both verbal and written.