MLOps recruitment
MLOps recruitment in Toronto and the GTA
Hire the engineers who take models from notebooks to reliable production systems.
Why MLOps hiring is hard
MLOps is a young discipline and few people hold the title. The right person may be working today as a DevOps engineer, a software engineer or a machine learning engineer.
The role needs both sides: enough machine learning to understand what a model needs, and enough infrastructure to run it reliably.
We look past the title to the work, and find people who have put models into production and kept them there.
Roles we recruit for
- MLOps Engineer
- ML Platform Engineer
- ML Infrastructure Engineer
- DevOps Engineer with ML experience
- MLOps team lead
How we vet MLOps candidates
We interview candidates on their work before we put them forward.
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Models in production
We ask which models they deployed, how, and what happened afterwards.
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Pipelines and automation
We check their experience with training, testing and release pipelines.
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Monitoring
We ask how they tracked model performance and what they did when it dropped.
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Working with data scientists
We note how they work with the people whose models they run.
What people say about working with Monika
From the recommendations on Monika Chopra’s LinkedIn profile. Read all of them
“Monika possesses expertise and understanding of the IT field and its underlying technologies which makes her great at matching talent with the right opportunities.”
John Poulakos “She has a very good understanding of technical recruitment. She can identify and suggest a good fit for your organization's needs.”
Nilesh Shah How we work
Six steps, from the first call to your new hire’s start date. See the full process
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Intake call
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Sourcing
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Technical vetting
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Shortlist
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Interviews
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Offer and onboarding
Hiring in MLOps?
Send us a few details about the role and we will call you to talk through the search.