Machine Learning Engineer Undefined

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.

THE ROLE

As a 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.

Your responsibilities will include:

• Taking vague requirements and translating them into models that solve real-world problems
• Running machine learning experiments using a programming language with machine learning libraries.
• Optimising solutions for performance and scalability.
• Implementing custom machine learning code.
• Data engineering, i.e. ensuring a good data flow between database and backend systems.
• Data science, i.e. analysing data and coming up with use cases
• MLOps, i.e. automating ML workflows with testing, reproducibility and metadata/feature storage; Designing ML architectures on Google Cloud

Requirements

• 1-3 years experience as an ML Engineer, ideally from a consulting background.
• This candidate should be comfortable working with python as a backend language, delivering code in well-tested CI/CD pipelines.
• Familiarity with cloud environments (Google Cloud, AWS, Azure).
• Experience with Software Engineering.
• Good knowledge of SQL.
• Knowledge of scaling up computations (GPUs, distributed computing, ..).
• Familiarity exposing ML components through web services or wrappers (e.g. Flask in Python).
• Strong communication and presentation skills.

Datatonic is an equal-opportunity employer. We’re committed to building an inclusive team that welcomes a diversity of perspectives, people, and backgrounds regardless of race, colour, national origin, gender, sexual orientation, age, religion, disability, citizenship, veteran status, or any other protected status. Our current team is made up of folks from very different backgrounds, including a former librarian, oceanographer and comic bookstore owner! If you are on the fence about whether you meet our requirements, we encourage you to apply anyway. Please reach out to us directly at join@datatonic.com if you need assistance or accommodation due to disability.