About the Company

We are a Scottish AI company backed by leading venture capital. We specialize in building bespoke AI solutions for Financial Services, focusing on tackling their most valuable challenges using targeted small language models.

Our mission is to accelerate AI’s time-to-value, enabling businesses to remain compliant, efficient, and secure while ensuring data stays within their environment. By leveraging knowledge distillation and small language models, we address complex regulatory workflows that general AI cannot solve.

Malted AI was founded on the innovative distillation techniques that earned its founders the 2022 Amazon Alexa Prize, triumphing over more than 100 global teams. Since then, we have raised £7 million from top-tier venture capital firms and are transforming how enterprises deploy AI at scale.

About the Role

📍 Location: Edinburgh (Relocation Assistance Available)
⏰ Job Type: Full-Time
Department: Software Engineering

Job Overview

We are looking for a Software Developer with a passion for cutting-edge technology and expertise in full-stack development. You will create scalable solutions in the cloud and translate research outputs into production-ready code. As a key part of our engineering team, you'll drive the development of our platform, build custom-made infrastructures to support the deployment of Machine Learning models at scale, and integrate our cutting-edge research findings into deployable code.

Key Responsibilities

• Architect, code, and maintain high-quality software solutions with an emphasis on clean, efficient, and maintainable code.
• Contribute to the development of robust, scalable, and secure software for our AI platform.
• Implement best practices and design to ensure high-quality software development.
• Support the translation of research output into deployable code.
• Implement testing, debugging, and optimization to ensure high performance, scalability, and reliability.
• Write comprehensive documentation for code, APIs, and system designs.

Key Requirements

• A minimum of 2 years of software engineering experience, with a strong portfolio of projects demonstrating coding abilities and technical problem-solving skills.

Preferred Requirements

• Track record of deploying solutions for enterprises.
• Experience working at deep tech companies involved in developing novel intellectual property (IP) and cutting-edge technologies.
• Familiarity with DevOps practices, CI/CD pipelines, and version control (Git).
• Knowledge of security best practices for software development.
• MSc degree in Computer Science, Software Engineering, AI, or a related field (or equivalent experience).
• Familiarity with machine learning frameworks (e.g., scikit-learn, PyTorch) or knowledge of AI principles is advantageous but not required.
• Contributed to public repositories or projects.

Benefits

• Competitive salary.
• Pension and stock options.
• Medical and life insurance.
• Combination of in-office and remote work with flexible and core team hours.
• Professional development and growth opportunities.
• Free snacks and drinks.
• Social events and company outings to build team cohesion.
• A dynamic and inclusive workplace culture that promotes innovation and teamwork.
• Chance to work on one-of-a-kind products at the forefront of the AI industry alongside a world-class team.

How to Apply

If you are ready to join a pioneering AI company and contribute to its success, we invite you to apply and be a part of Malted AI's exciting journey. Even if you feel that your background may not perfectly align with the described profile, we encourage you to apply if you possess a passion for technology and are eager to learn.

We believe in the potential for growth and development, and we are committed to providing support and resources to help you succeed in the role. Our positions are available for individuals with a valid UK work permit; at our current stage, we are not sponsoring visas.

We aren’t working with recruiters for these positions — we’re excited to connect directly with candidates who share our enthusiasm for small language models.