Machine Learning Engineer
Calendly - Remote - US
Posted Jan 20, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Machine Learning Engineer Remote - US What's in it for you? Ready to make a serious impact? Millions of people already rely on Calendly, and we're still in the midst of exciting product growth - it's a fantastic time to join us. Everything you'll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you've ever worked with, then we hope you'll consider allowing Calendly to be a part of your professional journey. About the team & opportunity What's so great about working on Calendly's Data Science & Machine Learning team? We make things possible for our customers through innovation in data, analytics and AI. Why do we need you? Well, we are looking for a Machine Learning Engineer who will deliver business value by executing the full machine learning lifecycle hands-on, from problem discovery through model deployment and monitoring. You will report to the head of Data Science & Machine Learning and will be responsible for building and operating ML-powered features that create magical experiences for our customers. Our team: - Drives business insights, strategic decision making, executive level and cross organizational business growth, and magical customer experiences for our end customers through impactful innovation. - Works closely with product, design, marketing, customer success, and engineering teams to implement ML models that improve the customer journey in service to growth and efficiency (for example, understanding the relationships among customers' behavior
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