As Google Cloud's premier partner in AI, Datatonic provides world-class businesses with cutting-edge data solutions in the cloud. We help clients take leading technology to the limits by combining our expertise in machine learning, data engineering, and analytics. With Google Cloud as our foundation, we help businesses future-proof their solutions, deepen their understanding of consumers, increase competitive advantage and unlock operational efficiencies. Our team consists of experts in machine learning, data science, software engineering, mathematics, and design. We share a passion for data & analysis, operate at the cutting edge, and believe in a pragmatic approach to solving hard problems. As a Machine Learning Engineer, you'll know how to engineer beautiful code in Python and take pride in what you produce.

As Google Cloud's premier partner in AI, Datatonic provides world-class businesses with cutting-edge data solutions in the cloud. We help clients take leading technology to the limits by combining our expertise in machine learning, data engineering, and analytics. With Google Cloud Platform as our foundation, we help businesses future-proof their solutions, deepen their understanding of consumers, increase competitive advantage and unlock operational efficiencies. Our team consists of experts in machine learning, data science, software engineering, mathematics, and design. We share a passion for data & analysis, operate at the cutting edge, and believe in a pragmatic approach to solving hard problems.

As an MLOps 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 an understanding of ML & Data Science fundamentals, as well as best software engineering practices such as automated testing and CI/CD.