This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud Platform. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world. As a Senior Machine Learning Engineer, you'll know how to engineer beautiful code in Python and take pride in what you produce. You'll be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes. Whilst the position is a hands-on technical role, we'd be particularly interested to find candidates with a desire to lead projects and take an active role in leading client discussions. Your responsibilities will involve building trusted relationships with prospects, finding creative ways to use machine learning to solve problems, scoping projects, and overseeing the delivery of these engagements. To be successful, you will need strong ML & Data Science fundamentals and will know the right tools and approach for each ML use case. You'll be comfortable with model optimisation and deployment tools and practices. Furthermore, you'll also need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI & Cloud.
Job Responsibility:
Translating Requirements: Interpret vague requirements and develop models to solve real-world problems
Data Science: Conduct ML experiments using programming languages with machine learning libraries
GenAI: Leverage generative AI to develop innovative solutions
Optimisation: Optimise machine learning solutions for performance and scalability
Custom Code: Implement tailored machine learning code to meet specific needs
Data Engineering: Ensure efficient data flow between databases and backend systems
MLOps: Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage
ML Architecture Design: Create machine learning architectures using Google Cloud tools and services
Engineering Software for Production: Build and deploy production-grade software for machine learning and data-driven solutions
Requirements:
Multiple years experience as a Machine Learning Engineer, preferably with a consulting background
Proficiency in Python as a backend language, capable of delivering production-ready code in well-tested CI/CD pipelines
Familiarity with cloud platforms such as Google Cloud, AWS, or Azure
Hands-on experience with foundational software engineering practices
Strong knowledge of SQL for querying and managing data
Experience scaling computations using GPUs or distributed computing systems
Familiarity with exposing machine learning components through web services or wrappers (e.g., Flask in Python)
Strong communication and presentation skills to effectively convey technical concepts