Senior Machine Learning Engineer
Description
Join our team and what we'll accomplish together
The AI Accelerator team is on a continuous journey towards helping TELUS become a world-class leader in data solutions, doing so by delivering data analytics capabilities built upon unified scalable platforms, advanced AI solutions, high-quality data, and a data-product-oriented culture while always keeping an eye on the horizon, preparing for the next big thing.
We are entrepreneurial and live by our AI Manifesto of failing fast and being outcome vs technology-driven, creating value for our customers, team members, communities, and the environment.
The team takes pride in our Artificial Intelligence and Machine Learning capabilities and takes ownership of each step of the process.
From hypothesis generation, initial exploring of datasets, developing novel AI techniques to discover insights, to developing automation pipelines and web visualizations, we do it all!
Always wanted to work with a team of innovators touching all business units within TELUS, and be part of a culture that embraces creativity and collaboration?
If so, we’d love to talk with you!
You’ll be a part of the team and journey that will transform the way we do business across various domains. You’ll collaborate with teams across the company, seeking out various data sources to help identify new business opportunities while championing data-driven decision-making and the accelerated adoption of AI.
As a Senior Machine Learning Engineer on the team, you will combine your expert knowledge of data science with your strong ML Ops and software development skills to automate and facilitate data exploration, analytics, machine learning model development, training and deployment and will leverage your experience in building reusable algorithms, functions and libraries.
What you’ll do
- Lead the iterative development, validation, and deployment of AI / ML models
- Collaborate on end-to-end automation efforts required to bring models to production
- Work with structured and unstructured raw data to design and develop innovative predictive models, metrics, and dashboards to uncover actionable insights
- Visualize and report data findings creatively in a variety of visual formats that provide insights to the organization
- Influence how we approach business challenges and opportunities by driving the adoption of a data-driven mindset
- Develop re-usable code aimed at delivering on future goals faster and more reliably
- Support and evolve the Advanced Analytics and Data Science roadmap by leveraging industry research, best practices and emerging tools / technology
- Build and maintain a strong engagement with key stakeholders to understand business needs and priorities
Qualifications
What you bring
- You are recognized for addressing business needs via your application of data mining and analysis, predictive modeling, statistics and other advanced analytical techniques in which you have previous hands-on work experience
- You are sought out for your skills in Machine Learning and AI, including regression, classification, clustering, time series analysis, NLP, and optimization and bring 4+ years of hands-on work and practical business experience in the above areas
- You are a master communicator capable of breaking down technical and complex concepts in a way that is understood by non-technical audiences
- You have advanced experience with Python and you are comfortable using various data science libraries such as Scikit-learn, Pandas, Numpy as well as frameworks like TensorFlow, Pytorch, Keras and have applied these skills towards solving actual business matters
- You are comfortable in and with a Jupyter environment and infrastructure, and familiar with GitHub
- You possess strong knowledge in SQL and distributed computing
- You are familiar with at least one of the cloud computing platforms - GCP, AWS, Azure
- You are well versed in software and AI development lifecycles, including ML Ops
- You are agile and have a bias for action, removing roadblocks to get results fast
Great-to-haves
- Masters or PhD degree in a quantitative field such as Math, Statistics, Computer Science, Economics, Engineering, or Data Science
- Experience with agile methodology and work in a start-up environment
- GCP or other cloud certifications
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