Lead AI​/Machine Learning Engineer

Job Description

What is the opportunity? This is an opportunity to work at RBC Insurance Active Data Platform team with a group of technology professionals dedicated to deliver solutions to Insurance business and clients. We are all in with Agile development, Dev Ops, Open Source, Software as a Service (SaaS) and modern tools and processes. You will have an opportunity to make a real difference by working on some impactful and meaningful projects.

We are looking for an enthusiastic and skilled Lead Machine Learning Engineer to spearhead our AI initiatives, lead the development and deployment of cutting-edge machine learning models, drive innovation, and collaborate with cross-functional teams to drive business growth and improvement. The candidate will have a strong background in machine learning models and algorithms, software development and leadership, with a proven track record of delivering high-quality solutions that meet business needs.

The person will play a key role in shaping our ML strategy and mentoring a team of talented engineers to reach the same goal.

The candidate posts deep understanding of data management principles, modern data stack, cloud computing and ability to apply them in practical, business-focused context. Partners across IT and with assigned business line(s) to assess, research, and analyze business, technical and system needs in order to resolve business systems issues. Recommends technology solutions that meet sponsor / stakeholder needs. Acts as primary IT liaison with multiple interfacing applications, third party vendors, IT Executives, and/or Project Managers.

Our applications are used by RBC staff and clients making your contributions highly impactful and visible, directly contributing to the success of RBC. We deliver digitally enabled applications that are both internal and internet facing. We build Cloud Data Lakehouse, stable web, and back-end applications which are resilient, scalable and high performance that avoids failure and focused on delivering best client experience.

We continuously update our tech skills and upgrade our platforms to match industry standards.
What will you do?

Technical Leadership
: lead a team of machine learning engineers and data scientists, and provide technical guidance, mentorship, and oversight.

Collaboration: partner with Agile project team members, project product managers, product owners, software engineers, and stakeholders to evaluate, review use cases, align ML initiatives with overall company goals.

MLOps
: design, build, and deploy scalable machine learning models and algorithms that address business needs, with a focus on performance and reliability. Oversee the setup and maintain of end-to-end machine learning pipelines to ensure integration with applications. Collaborate with data engineers to ensure efficient data collection, preparing and feature engineering pipelines.

Documentation
: set up standards and processes, maintain and keep up to date comprehensive documentation of application architecture, models, pipelines, and development processes.

Reviews: set up coding best practices, ensure high-quality code through regular reviews and all solutions meet the RBC’s coding standards.

Operations
: keep software engineering practice in mind, build products that can be maintain with least incidents, maintain metrics and monitoring to meet Service and Operational Level Agreements.

Emerging Technology
: stay up-to-date with the latest advancements in machine learning and related emerging technologies, share knowledges with teams and apply the knowledge to improve existing systems and develop new ones.

What do you need to succeed?
Must Have

Strong programming skills in languages such as Python, java, or C++. Experience with cloud platforms (AWS, GCP, and Azure) and MLOps tools.

3+ years of hands-on experience in machine learning development, and experience leading a team of machine learning developers or engineers.

Strong understanding of software development principles, including design patterns, testing, and deployment. Experience with Dev Ops practices such as CI/CD, experience with containerization using Docker and Kubernetes.

Pas…