Applied Machine Learning Engineering Managers
Job Description
Description
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Applied Machine Learning Engineering Managers
- Remote – Americas
- Engineering & Data
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About the role
About the role
Welcome to Shopify’s engine room of innovation. As an Applied Machine Learning Engineering Manager, you will lead teams in crafting groundbreaking ML solutions that redefine connections between millions of merchants and buyers. Your role is to guide ML engineers in making strategic decisions that advance LLMs, agents, and address large-scale real world problems. With a focus on developing extensive models, enhancing search, refining recommendations, and personalizing experiences, your leadership will transform what’s currently considered possible in the space of AI-driven commerce.
Key Responsibilities:
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Lead teams to design, refine, and deploy ML models that revolutionize commerce solutions.
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Spearhead initiatives integrating LLMs, agents, and multimodal models into Shopify’s ecosystem.
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Apply machine learning techniques to real world problems by enhancing optimized search and personalized recommendations.
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Cultivate a collaborative culture emphasizing technical excellence, learning, and innovation.
Qualifications:
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Extensive experience managing teams to implement large-scale ML models.
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Proficiency in TensorFlow or PyTorch, and strong Python skills.
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Proven problem-solving skills in complex, real-world product environments.
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Excellent communication skills with a track record of thriving in dynamic settings.
Ready to lead on the bleeding edge of AI? Join the team that’s making commerce better for everyone.
At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, coming prepared with your own IDE.
This role may require on-call work.
About Shopify
Opportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. We propel entrepreneurs and enterprises to scale the heights of their potential. Since 2006, we’ve grown to over 8,300 employees and generated over $1 trillion in sales for millions of merchants in 175 countries.
This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.
About you
Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.
Before you apply, consider if you can:
- Care deeply about what you do and about making commerce better for everyone
- Excel by seeking professional and personal hypergrowth
- Keep up with an unrelenting pace (the week, not the quarter)
- Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
- Bring critical thought and opinion
- Use AI tools reflexively as part of your fundamental workflow
- Embrace differences and disagreement to get shit done and move forward
- Work digital-first for your daily work
Shopify
We hire people, not resumes. If you think you’re right for the role, apply now.
Apply Now
First things first
We want to ensure you’re the type of person who will thrive here so we can move you quickly through our hiring process. Before completing the job application, please check all the statements that apply to you below:
I care deeply about what I do
I am always seeking new (sometimes uncomfortable) growth
I thrive on change in an ambiguous environment
I get shit done and can keep pace to ship weekly
I want to work remotely for my daily work
I have a history of being resilient and resourceful
I want to make commerce better for everyone
It looks like you might not be a great fit for Shopify at this time — while we encourge everyone to apply, we are looking for someone who can meet all these criteria.
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Which track are you interested in pursuing with Shopify?*
Individual ContributorPeople Manager
How many years of hands-on ML modeling and development do you have? (Not including academic experience or internships)*
0-4 years5-7 years8-10 years11+ years
How would you describe your comfort with Object Oriented Programming?*
I am still learning but with support can code in OOPI work more efficiently in another type of programmingI am comfortable and confident I would do well in an Object Oriented Pair Programming interviewI am an expert
What parts of the Model Development Lifecycle have you managed?
Problem definition, data collection and trainingResearch, feature engineering tuning, training, deployment, maintenanceTuning, training, interpretation and production
As an ML Engineer, how would you describe your experience on projects?*
I haven’t led a project yet, but I’ve contributed to the tasks assigned to me and learned from the process.I’ve led a small project or a part of a larger project from start to finish.I’ve led multiple projects across teams and stakeholders, and was accountable for the project’s success.I’ve led high-stakes projects spanning multiple stakeholders, disciplines, and technical complexities.
As an ML Engineer, how would you describe your approach to mentorship?*
I’m still learning the ropes, so I tend to focus more on absorbing knowledge myself.I’m comfortable with my skills, but I still rely on more experienced engineers for complex problems.I mentor others and promote a culture of learning and growth within the organization.I mentor others, and play a role in increasing the technical competencies of my craft at the org level.
What are trends in ML that you are following or have experimented with on your own?*
Describe the impact you have had on the company and customers of your current or most recent role?*
Give an example of an ML project that you led. Specify what parts of this you did by yourself*
Which models are you comfortable using to determine feature importance?*
Linear Regression Decision trees Deep Learning All of the above
Please confirm you’ve read and agree with our candidate NDA *
Please confirm you’ve read our applicant privacy notice *
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Company
Vector Institute
Location
, ON, Canada
Country
Canada
Salary
125.000
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