Engineering Manager, Machine Learning

The Role of Engineering Manager, Machine Learning at Overstory

As an ML Engineering Manager at Overstory, you will lead across several cross-functional teams, managing up to approximately 10 machine learning engineers and data scientists. Your role is pivotal in supporting teams that work on data- and machine-learning-driven product capabilities. Our product teams are cross-functional, typically including product managers, designers, engineers, and subject matter experts relevant to the team's domain.

You will be accountable for the technical direction and delivery outcomes within your area. You are expected to challenge your teams to pursue ambitious goals while providing a high level of support, fostering engineering talent, and creating a highly collaborative, team-based environment where exceptional work can thrive.

Your primary focus will be on building high-performing teams and driving results through others. While you won't spend significant time on hands-on coding, you are expected to dive deep technically when necessary and leverage your experience to support robust technical decision-making.

What You Will Do

• Enable our Machine Learning and data teams to operate as highly productive, cross-functional units delivering high-quality ML-driven capabilities.
• Support teams working with satellite imagery and geospatial datasets, skillfully balancing experimentation, iteration, and continuous improvement of existing solutions.
• Grow the teams by attracting and hiring exceptional Data and ML talent.
• Foster an inclusive, supportive, and caring culture where everyone is empowered to do their best work.
• Provide regular 1:1 coaching and constructive feedback to help team members thrive, grow, and achieve their career aspirations.
• Act as a strategic partner to Product Managers within your domains, ensuring technical decisions effectively balance short- and long-term goals.
• Ensure the technical approaches within your domains support future product and modelling needs.
• Work closely with other Product, Design, and Engineering leaders on strategy, technology, and people development.
• Help evolve Data and ML practices, introducing methodologies that enhance collaboration, delivery, and learning across the organization.

About You

• 8+ years of professional experience building ML- or data-driven systems, with at least 3 years' experience leading and managing ML or data-focused teams.
• A deep passion for climate and a belief in the pivotal role technology can play in addressing environmental challenges.
• Experience working effectively in a high-growth scale-up or startup environment.
• Product-minded, with a proven ability to demonstrate meaningful business impact through technology solutions.
• Sufficient technical depth in machine learning, data systems, or applied ML to confidently guide teams and challenge decisions.
• Experience working with Python-based ML or data workflows and collaborating closely with data scientists.
• Strong leadership skills, characterized by a coaching mindset and the ability to support engineers and data scientists at all levels.
• Excellent communication skills and the ability to collaborate effectively in diverse, cross-functional environments.
• A passion for continuous learning and staying current with evolving technologies and industry trends.

Nice to Haves

• An engineering mindset or background, with experience applying software engineering best practices to data and ML systems (e.g., reproducibility, testing, monitoring, and production deployments).

If you don’t meet all of the above yet feel you have lots to offer, please apply anyway.

What You Get

• To be part of truly mission-driven work that actively reduces wildfires, protects earth’s natural resources, and helps solve our climate crisis.
• A flexible working environment with significant autonomy, allowing you to build your work days around your life.
• Access to valuable benefits such as a remote working budget, an educational budget, and dedicated time to develop new skills.
• The opportunity to be surrounded by an excellent, vibrant, and smart team that fosters mutual support and believes in a culture of openness, tolerance, and respect.
• Equity and a competitive salary package.

About Our Team

We are a global team of 100 people from diverse backgrounds and 15 nationalities, working remotely from eleven different countries. We are actively seeking candidates who reside and work in one of these countries: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Denmark, Switzerland, and Canada. We organize an annual in-person team gathering for memorable collaboration and connection, with options for occasional in-person meetups throughout the year.

Diversity & Inclusion

At Overstory, we place enormous value on diversity and inclusion, striving to continually bring in people of all genders, races, creeds, ethnicities, abilities, and backgrounds. We firmly believe that the best ideas emerge when individuals with different perspectives and approaches collaborate on a shared problem. We are committed to further diversifying our team, and we are proud that four out of nine members of our leadership team are female, 46% of our overall team are female, and 20% of the team are people of color. Our team collectively speaks fifteen languages.

Our Values

• Tackling the climate crisis is our greatest mission. We act with urgency.
• Our curiosity fuels our growth. We recognize that change is constant, and we find joy and power in exploration.
• We’re rooted in diversity. Just as ecosystems need biodiversity to thrive, our resiliency comes from our differences.
• We Care For Each Other. We love the power of machines but we nurture each other as humans.
• Trust is fundamental. We assume the best in everyone, and we share ideas openly so that we have a positive impact.

Key skills/competency

• Machine Learning
• Data Science
• Engineering Management
• Team Leadership
• Python ML Workflows
• Geospatial Data
• Satellite Imagery Analysis
• Product Strategy
• Technical Decision-making
• Climate Technology