Kraken - Senior Machine Learning Engineer
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• ~3 years of professional experience as a Machine Learning Engineer or similar applied ML role. • Strong Python skills and experience with common ML libraries and frameworks. • Practical experience taking ML models from development into production. • Good understanding of software engineering fundamentals (version control, testing, CI/CD etc).Experience working with cloud infrastructure and data pipelines. • An ability to explain ML concepts clearly to non-ML engineers.A bias towards action, learning quickly, and improving systems over time. • Prior experience building internal platforms or shared tooling. • Exposure to MLOps practices, including model monitoring, evaluation, and deployment automation. • Familiarity with considerations regarding data privacy, security, or responsible AI. • Kraken is a certified Great Place to Work in France, Germany, Spain, Japan and Australia. In the UK we are one of the Best Workplaces on Glassdoor with a score of 4.5 and in Germany we rate 4.7 on Kununu as a Top Company. Check out our Welcome to the Jungle site (FR/EN) to learn more about our teams and culture. • Are you ready for a career with us? We want to ensure you have all the tools and environment you need to unleash your potential. If you have any specific accommodations or a unique preference, please contact us at [email protected] and we'll do what we can to customise your interview process for comfort and maximum magic!
Responsibilities
• Develop and implement machine learning models to solve complex problems within the organization's AI Foundations project scope. • Collaborate with cross-functional teams including data scientists, software engineers, product managers, and business analysts on various aspects of projects related to backend engineering for artificial intelligence applications. • Analyze large datasets using statistical methods and machine learning algorithms to extract insights that inform decision making within the organization's AI Foundations project scope. • Design, develop, test, deploy, monitor, optimize, troubleshoot, maintain, document, and improve existing or new artificial intelligence systems for backend engineering purposes in alignment with organizational goals and objectives related to its AI Foundations projects. • Participate actively in the organization's project management processes by defining scope of work, setting timelines, assigning tasks, monitoring progress, reporting status updates, resolving issues that arise during development or deployment phases within the context of backend engineering for artificial intelligence applications and ensuring successful delivery on time with high quality. • Communicate effectively both verbally and in writing to internal stakeholders such as team members, managers, clients, partners, vendors, suppliers, regulators, government agencies or other external parties within the organization's AI Foundations project scope related to backend engineering for artificial intelligence applications. • Stay up-to-date with industry trends and best practices in machine learning by attending conferences, workshops, webinars, training sessions, reading relevant publications, participating in online communities of practice or engaging in other professional development activities within the organization's AI Foundations project scope related to backend engineering for artificial intelligence applications. • Mentor and coach junior engineers on various aspects such as machine learning algorithms, data preprocessing techniques, model selection criteria, performance evaluation metrics, deployment strategies, security considerations or ethical issues in developing solutions within the organization's AI Foundations project scope related to backend engineering for artificial intelligence applications. • Provide technical leadership and guidance by reviewing code quality standards, architectural designs, system requirements specifications, test plans, user stories, acceptance criteria, deployment strategies, security considerations or ethical issues in developing solutions within the organization's AI Foundations project scope related to backend engineering for artificial intelligence applications. • Collaborate with cross-functional teams including data scientists, software engineers, product managers, business analysts on various aspects of projects related to backend engineering for artificial intelligence applications and provide technical leadership by reviewing code quality standards, architectural designs, system requirements specifications, test plans, user stories, acceptance criteria, deployment strategies or security considerations in developing solutions within the organization's AI Foundations project scope. • Participate actively in agile development processes such as s
No credit card. Takes 10 seconds.