Machine Learning Engineer
Microsoft
Machine Learning Engineer
Vancouver, British Columbia, Canada
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Overview
Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world.
Microsoft Defender for Endpoint (MDE) is a product for preventative protection, post-breach detection, automated investigation, and response. Our team, the core machine learning and data science team, is responsible for building ML, LLM, and automation solutions that defend over a billion end users and enterprises from cybersecurity attacks through Microsoft Defender AntiVirus, Microsoft Defender Endpoint Detection and Response, and Network Protection. We are a mix of machine learning engineers, data scientists, data engineers, and security researchers who develop big data pipelines, run experiments, and deploy our protection to production to protect customers at scale.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Qualifications
Required Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND relevant internship experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- OR equivalent experience
- 1+ years of experience working on bringing machine learning pipelines to production systems.
- 1+ years of experience developing large-scale data pipelines, utilizing either distributed data processing frameworks (e.g., Apache Spark, Hadoop), real-time data streaming platforms (e.g., Kafka), or query languages like SQL and KQL.
- 1+ years of experience with classical machine learning application (eg Logistic Regression, LightGBM, XGBoost, etc) or custom deep-learning approaches using PyTorch or similar technology.
- 1+ years of experience with Large Language Models (LLMs).
Other Requirements:
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check:
- This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Microsoft Cloud Background Check:
Preferred Qualifications:
-
Bachelor's Degree (or currently pursuing) in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree (or currently pursuing) in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
OR equivalent experience
- Cybersecurity experience
- 1+ years of experience developing on at least one major cloud platform (e.g., Azure, AWS, GCP).
- 1+ years of experience in MLOps, including model deployment, monitoring, version control, and continuous integration/continuous delivery (CI/CD) pipelines for machine learning projects, using tools such as Azure Machine Learning, MLflow, Kubeflow, TensorFlow Serving, or similar.
Applied Sciences IC2 - The typical base pay range for this role across Canada is CAD $67,100 - CAD $131,400 per year.
Find additional pay information here:
https://careers.microsoft.com/v2/global/en/canada-pay-information.html
Microsoft will accept applications for the role until July 12, 2025.
#MSFTSecurity #machinelearning #mlops #cybersecurity
Responsibilities
- Design, develop, and maintain the machine learning data platform that powers cybersecurity protection machine learning models in our products and services.
- Collaborate with others to identify opportunities to optimize data tools used to transform, manage, and access data across teams. Ensures the effectiveness and placement of performance monitoring protocols across multiple data pipelines.
- Propose, design, experiment, and implement machine learning designs to protect our customers.
- Experiment with and apply large language models and agentic systems to protect our customers and improve our internal systems.