Lead Machine Learning Scientist

RBC • Toronto, ON

2d • Onsite

About The Position

As a Lead Machine Learning Scientist, you will drive the development of advanced Python-based solutions to extract actionable insights from RBC’s infrastructure data, enabling faster incident resolution and reducing Mean Time to Recovery (MTTR). Your expertise in Large Language Models (LLMs) and automation will enhance operational efficiency by streamlining data analysis and workflow processes. Collaborating with cross-functional teams, you will design and implement innovative machine learning models to monitor infrastructure health, predict potential issues, and optimize system performance. This role offers a unique opportunity to lead cutting-edge initiatives in a dynamic, high-impact environment.

Requirements

• Design and implement advanced Python-based machine learning models to analyze infrastructure data and extract actionable insights.
• Leverage Large Language Models (LLMs) and explore tools like Ollama to enhance data interpretation and streamline operational workflows.
• Develop and deploy automation solutions to monitor infrastructure health, predict potential issues, and reduce Mean Time to Recovery (MTTR).
• Analyze and interpret operational data from systems like ServiceNow to identify patterns, optimize processes, and improve system stability.
• Apply software engineering principles to build scalable, efficient, and maintainable pipelines for data processing and model deployment.
• Collaborate with cross-functional teams to align machine learning solutions with organizational goals and infrastructure needs.

Nice To Haves

• Experience with GitHub Actions to automate CI/CD pipelines for seamless integration and deployment of solutions.
• Familiarity with database technologies such as Postgres, SQL, MSSQL, and ELK Stack (Elasticsearch, Logstash, Kibana)
• Exposure to cloud-native platforms like OpenShift Container Platform (OCP)
• Knowledge of system architecture and experience working with distributed systems to enhance infrastructure performance.

Responsibilities

• Design and implement advanced Python-based machine learning models to analyze infrastructure data and extract actionable insights.
• Leverage Large Language Models (LLMs) to enhance data interpretation and streamline operational workflows.
• Develop and deploy automation solutions to monitor infrastructure health, predict potential issues, and reduce Mean Time to Recovery (MTTR).
• Analyze and interpret operational data from systems like ServiceNow to identify patterns, optimize processes, and improve system stability.
• Collaborate with cross-functional teams to align machine learning solutions with organizational goals and infrastructure needs.
• Drive innovation by researching and applying cutting-edge machine learning techniques to solve complex infrastructure challenges.
• Build scalable and efficient pipelines for data processing and model deployment to ensure reliable and timely insights.
• Provide technical leadership and mentorship to team members, fostering a culture of continuous learning and improvement.

Benefits

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high-performing team
• Flexible work/life balance options
• Opportunities to do challenging work
• Opportunities to take on progressively greater accountabilities

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed