Rapid7 AI Engineer II - ML Ops 

United Kingdom, Northern Ireland, Belfast 

34806997

We ensure AI, ML and data science are applied in a meaningful way to add customer value, best achieve business objectives and deliver ROI. Unnecessary complexity is avoided and we adopt a creative, fast-fail, highly iterative approach to accelerate ideas from proof-of-concept to go or no-go. Our current capabilities are built on 20+ years of threat analysis and open-source communities with, 40 AI patents granted and 20+ pending. However, we’re just getting started!

The make-up of the group is such that our technical skills complement one another. No one can be an expert in everything - we share our AI, ML and data science knowledge between ourselves plus are creating an in-house AI Learning & Development plan.

About the Role

An AI Engineer II in MLOps designs and implements systems to support and enable AI research, systems to accelerate and augment AI model development, and systems that bring AI features to our product portfolio. You will build these systems in the cloud, using standard MLOps and DevOps tools, and will work closely with the other members of the COE to build custom infrastructure where appropriate. This is important work and speed to market is key - you’ll work fast and smart, supported by more senior members of the team, getting results that let us make decisions about how best to deliver our work to our customers.

You will:

• Design and build infrastructure to support AI/ML/data science models with a focus on delivering customer value.
• With guidance and direction, you are able to explore, research and tackle problems while building up your knowledge.
• Take responsibility for the quality of your own work and help impact the work of others too.
• Be a first-class stakeholder in all parts of the AI MLOps R&D process.
• Create productive cross-functional relations with teams like engineering, UX, customer research and product management.
• Provide informal guidance to new team members.

What we’re looking for technically:

• Good conceptual knowledge of a cloud-based infrastructure and continuous integration and delivery (CICD). It’s a broad area; we do not expect you to be across it all.
• More specifically, building services and APIs using Python, using Terraform to manage cloud resources, and containerisation with Docker.
• Some experience with cloud based AI/ML tools (e.g. AWS SageMaker) and MLOps tools (e.g. MLFlow)
• As a bonus, a degree in software engineering.
• Any cybersecurity expertise is also a bonus - or maybe your experience comes from capital markets, online marketplaces, healthcare, social media, insurance, or somewhere else.

And you as a person:

• Bring a positive, can-do, solution-oriented mindset, welcoming the challenge of tackling new problems.
• Are persistent and consistent.
• Enjoy working in a fast-paced environment.
• Understand the highly iterative nature of AI development and the need for rigour.
• Appreciate the importance of thorough testing and evaluation to avoid production issues.
• Are a great teammate to help peers become stronger problem solvers, communicators, and collaborators.
• Have a curiosity and passion for continuous learning and self-development.
• Stay open-minded, listening to new ideas and suggestions from colleagues, carefully considering and sometimes adopting them.
• Realise the importance of wider ethical and risk considerations with AI.
• Possess good interpersonal and communication abilities, explaining hard-to-understand topics to different audiences and writing up work clearly.
• Exhibit a bias for action, without being careless.