Machine Learning Engineer
Job Summary:
As a Machine Learning Engineer, you will work with other smart and talented individuals to deliver high-quality data science and machine learning outcomes to clients. Our projects and clients vary greatly, but here's a typical snapshot of some of your responsibilities:
• Selecting the best technology for a given data science use case
• Choosing the best operational architecture for a ML application
• Developing ML applications
• Applying MLOps principles to data science workflows, e.g., building reproducible training pipelines
• Standing up cloud services to run ML workloads
• Automating repeatable routines in ML workflows
• Providing consulting services that combine architectural vision with hands-on technical experience using some of the latest AI/ML tools and methods
• Supporting pre-sales activities including conversations, presentations, and writing proposals
• Contributing to thought leadership activities, including blog and brown-bag content, for the wider AI/ML community
Requirements:
The ideal candidate should have:
• Commercial software development experience across different industries and organisations
• Commercial experience of machine learning application development
• Production experience in at least one cloud stack
• Consulting experience, either with external clients or internally within an organisation
• Fundamental modern software engineering skills (can design and implement a well-structured code base and software development cycle, including CI/CD, TDD, monitoring/logging)
• Solid programming skills in at least one applicable language, such as Python
• Cloud engineering skills to architect, use, and deploy cloud services in at least one cloud stack
• An understanding of key machine learning and data science concepts across different areas
• A good grasp of concepts in machine learning development cycle & MLOps, such as model development, model deployment, data versioning etc.
• Evidence of ML project delivery or self-learning that can be demonstrated
• Exposure to one or more ML technologies and/or frameworks such as Amazon Sagemaker, Google AI Platform, Databricks / mlfow, AI API Services, and/or TensorFlow, Pytorch, Scikit-Learn etc, with demonstrable production experience
• The ability to search and evaluate the best tool for a range of different technical problems
What We Offer:
We value diverse skill-sets and do not necessarily require all the above. However, we believe in supporting our team to take their career in a direction that aligns with their passions. You'll get all the tools you need to hit the ground running, including a new phone, laptop & swag. Our My Deal program allows you to tailor your yearly plan, with the support of your Leader, to decide on what's most important to you. This might include extra professional development, extra annual or parental leave, time to work on your side hustle, or something else completely different.