Senior Machine Learning Engineer (AI)

Location: Mountain View, San Francisco, or Austin, United States; remote work is available in countries where hirify.global has a legal entity. Office, home-based, and combined work arrangements are supported.

Base salary in the United States: $206,100–$269,075 in Zone A, $185,490–$242,168 in Zone B, or $171,063–$223,332 in Zone C, plus possible benefits, bonuses, commissions, and equity.

Company

hirify.global develops software products that help teams collaborate and manage different types of work.

What you will do

• Develop and implement advanced machine-learning algorithms for business-critical applications.
• Build scalable, reliable forecasting models, including deep-learning models, for granular company top-line metrics.
• Lead the full machine-learning lifecycle, from problem definition and data preparation through deployment and iteration.
• Design production-quality model and system architectures, infrastructure, and modeling applications.
• Evaluate model quality and translate complex business problems into practical solutions with Growth, GTM, Product, Finance, Sales, analytics, and engineering stakeholders.
• Explain technical recommendations clearly and provide mentorship to junior machine-learning engineers.

Requirements

• Senior-level experience developing and deploying machine-learning solutions.
• Experience with forecasting models, deep learning, model evaluation, and production machine-learning systems.
• Ability to work across experimentation, data preparation, modeling, deployment, and continuous improvement.
• Ability to collaborate with technical and non-technical stakeholders and communicate machine-learning concepts clearly.
• Work must be performed in a country where hirify.global has a legal entity, or from one of the listed United States locations.

Culture & Benefits

• Flexible office-based, home-based, and combined work arrangements.
• Virtual interviews and onboarding within a distributed-first organization.
• Health and wellbeing resources.
• Paid volunteer days and additional benefits supporting employees, families, and local communities.
• Possible bonuses, commissions, and equity in addition to base pay.

Hiring process

• Interviews and onboarding are conducted virtually.
• Identity verification may be required as a condition of employment.