Engineering Manager, Machine Learning

Location: Remote from the United States, Canada, United Kingdom, the Netherlands, Denmark, Estonia, France, Ireland, Portugal, Sweden, or Switzerland. Working hours must overlap with Europe (GMT/WET, CET, EET) or Eastern North America (NST, AST, EST).

Company

hirify.global develops AI and satellite-imagery technology that helps electric utilities identify vegetation risks, prevent outages, reduce wildfire risks, and build a more resilient grid.

What you will do

• Lead cross-functional machine learning and data teams of up to approximately 10 machine learning engineers and data scientists.
• Set technical direction and drive delivery outcomes for data- and machine-learning-driven product capabilities.
• Support work with satellite imagery and geospatial datasets, balancing experimentation, iteration, and continuous improvement.
• Build and grow teams by hiring, coaching, and developing ML and data talent.
• Partner with Product, Design, and Engineering leaders on strategy, technology, technical decisions, and people development.
• Improve data and ML practices, collaboration, delivery, and organizational learning.

Requirements

• 8+ years of professional experience building machine-learning- or data-driven systems.
• At least 3 years of experience leading and managing ML- or data-focused teams.
• Technical depth in machine learning, data systems, or applied ML sufficient to guide teams and challenge decisions.
• Experience with Python-based ML or data workflows and close collaboration with data scientists.
• Strong leadership, coaching, communication, and cross-functional collaboration skills.
• Experience in a high-growth scale-up or startup environment and a product-minded approach focused on business impact.

Nice to have

• Engineering background and experience applying software engineering practices to data and ML systems, including reproducibility, testing, monitoring, and production deployments.

Culture & Benefits

• Flexible, autonomous, and collaborative remote environment built around trust.
• Home office stipend, coworking budget, and ongoing education budget.
• Annual in-person team gathering and optional in-person collaboration meetups.
• Mission-driven work focused on reducing wildfires, protecting natural resources, and addressing the climate crisis.
• Inclusive culture centered on diversity, curiosity, care, and open sharing of ideas.