Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in securing the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.

Assignment Description:

We are looking for a Senior Machine Learning Engineer to join our dynamic team.

What you will work on:

• Develop AI/ML software products, from exploring large datasets, applying new algorithms, and feature engineering, to testing, evaluating, and deploying models for production usage.
• Build, maintain, and scale large-scale data infrastructure to support AI/ML projects, ensuring it is robust, scalable, and maintainable.
• Contribute to software architecture decisions and the technical roadmap by applying software design patterns and best practices for scalable, maintainable, and future-proof code.
• Develop reusable components, services, and frameworks that address common AI/ML needs, including feature reuse, model traceability, monitoring, A/B testing, versioning, and release management.
• Serve both online inference endpoints and batch inference solutions for scalable deployment of AI/ML models.
• Work closely with cross-functional agile teams of engineers, data scientists, and business stakeholders to build a strong AI ecosystem within the company.

What you bring:

• BSc or MSc degree in computer science, engineering, or a related field, or equivalent practical experience.
• 5+ years of professional experience in a senior Machine Learning Engineer role, with proven success in deploying ML solutions at scale in larger organizations.
• Strong software engineering skills with hands-on experience in coding, following DevOps principles, and applying software engineering best practices to ML projects.
• Extensive experience with Python programming (4+ years), including the development of AI/ML products that are production-ready, secure, and performance-optimized.
• Solid expertise in cloud technologies for ML development, particularly Google Cloud Platform and Vertex AI.
• Deep understanding of MLOps practices, including the development of ML pipelines, data pipelines, and deploying ML applications into production environments.
• Strong working knowledge of various AI/ML techniques and frameworks.
• Experience handling large-scale, heterogeneous data (both batch and stream), including hands-on development with DBT and a strong grasp of cloud data storage technologies and data quality management.
• Experience in requirement alignment, solution design, task breakdown, mentoring team members, and ensuring adherence to organizational standards and best practices.
• Familiarity with agile methodologies, data-driven development, and team collaboration tools and practices.