Software Engineer - ML Platform

📋 Description

• • Join Veriff's dynamic ML Platform team as a Software Engineer, where you will play a pivotal role in constructing the foundational infrastructure that empowers rapid, compliant, and reliable iteration on cutting-edge machine learning products.
• • This is an exceptional opportunity to contribute to a team that is building scalable, observable, and user-friendly systems essential for managing vast datasets, training sophisticated models, rigorously evaluating performance, and deploying these models at scale.
• • Having successfully established core platform capabilities, Veriff is now entering an exciting high-growth phase. Your contributions will be instrumental in driving systemic excellence, focusing on institutionalizing world-class observability, optimizing for cost-efficiency, and radically accelerating experimentation speed.
• • You will act as a crucial bridge, connecting architectural vision with a seamless and intuitive developer experience for our internal data science teams.
• • Your responsibilities will encompass implementing robust Observability Frameworks, developing the essential tools and templates that provide deep visibility into model performance, data drift, and training statistics, thereby ensuring the resilience and reliability of our continuous retraining loops.
• • You will engineer for efficiency by developing sophisticated systems designed to meticulously track and optimize compute costs and training performance, enabling Veriff to scale its machine learning initiatives sustainably and cost-effectively.
• • A key aspect of your role will involve building advanced Experimentation Tooling, executing on a strategic roadmap for internal tools that empower Data Scientists and ML Engineers to iterate and deploy experiments with minimal friction, fostering a culture of rapid innovation.
• • You will be instrumental in developing SaaS-grade ML Services, writing high-quality, maintainable Python code to build and automate critical services that form the backbone of our ML lifecycle.
• • You will serve as a bridge-builder, working closely with our Staff Engineer to translate architectural designs into tangible implementations and collaborating effectively with SRE/DevXP teams to guarantee our solutions are production-ready, robust, and easily managed.
• • This role demands a proactive and collaborative approach, working within a talented team dedicated to advancing the state-of-the-art in ML infrastructure.
• • You will contribute to a culture of continuous improvement, seeking out opportunities to enhance existing systems and introduce innovative solutions.
• • The work involves tackling complex technical challenges in a fast-paced, growth-oriented environment.
• • You will gain exposure to a wide range of ML technologies and best practices, contributing to Veriff's position as a leader in identity verification.
• • Your efforts will directly impact the speed and quality of ML-driven product development across the organization.
• • You will be part of a team that values technical excellence, collaboration, and a strong product mindset for internal tooling.
• • The role offers significant opportunities for professional growth and development within a rapidly expanding tech company.
• • You will be empowered to take ownership of projects and drive them from conception to deployment.
• • You will contribute to building a scalable and reliable ML platform that supports Veriff's global operations.
• • Your work will directly influence the efficiency and effectiveness of Veriff's machine learning initiatives.
• • You will collaborate with cross-functional teams to understand their needs and translate them into technical requirements for the ML platform.
• • You will be involved in the entire software development lifecycle, from design and implementation to testing and deployment.
• • You will help shape the future of ML infrastructure at Veriff, contributing to strategic technical decisions.
• • The role requires a strong understanding of software engineering principles and best practices, applied within the context of machine learning systems.
• • You will be responsible for ensuring the security, scalability, and maintainability of the ML platform components you develop.
• • You will contribute to documentation and knowledge sharing within the team and the wider engineering organization.
• • This is a hands-on role where you will be writing code and directly contributing to the platform's development.
• • You will have the opportunity to work with modern cloud technologies and MLOps tools.
• • You will be part of a company that is at the forefront of identity verification technology, making a real-world impact.