Hiring.Camp

Engineering Manager, Machine Learning

Overstory

·

Dec 18, 2024

Location
United States | Canada | United Kingdom | The Netherlands | Denmark | Estonia | France | Ireland | Portugal | Sweden | Switzerland · Amsterdam, North Holland, Netherlands
Workplace
Remote
Department
Engineering
Seniority
Manager
Experience
8+ years
Source
Greenhouse

Description

The climate crisis is the defining challenge of our time—but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting-edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes.

The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change. 

One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines. 

That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid.

Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers—15 nationalities strong and growing. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good.

Join us to help us build a more resilient world together. 

The role

As an ML Engineering Manager, you will lead across several cross-functional teams, managing up to ~10 machine learning engineers and data scientists. You will support teams working on data- and machine-learning-driven product capabilities.

Our product teams are cross functional and will typically include product managers, designers, engineers and subject matter experts relating to the team’s domain.

You will be accountable for the technical direction and delivery outcomes of your area. You will challenge your teams to pursue ambitious goals while providing a high level of support — growing engineering talent and fostering a highly collaborative, team-based environment where people can do great work.

Your primary focus will be on building high-performing teams and driving results through others. You will not be expected to spend significant time doing hands-on coding; however, you will be expected to dive deep technically when required and leverage your experience to support strong technical decision-making.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What you will do 

  • Enable our Machine Learning and data teams to operate as highly productive, cross-functional teams delivering high-quality ML-driven capabilities
  • Support teams working with satellite imagery and geospatial datasets, balancing experimentation, iteration, and ongoing improvement of existing solutions
  • Grow the teams by attracting and hiring great Data and ML talent
  • Foster an inclusive, supportive, and caring culture where everyone can do their best work
  • Provide regular 1:1 coaching and feedback to help others thrive, grow, and reach their aspirations
  • Act as a strategic partner to Product Managers within your domains, ensuring technical decisions 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
  • Help evolve Data and ML practices and introduce ways of working that improve collaboration, delivery, and learning

About You  

  • 8+ years of professional experience building ML- or data-driven systems, at least 3 years’ experience leading and managing ML or data-focused teams
  • Passionate about climate and the role technology can play in addressing environmental challenges
  • Experience working in a high-growth scale-up or startup environment
  • Product-minded, with the ability to demonstrate meaningful business impact through technology
  • Sufficient technical depth in machine learning, data systems, or applied ML to guide teams and challenge decisions
  • Experience working with python-based ML or data workflows and collaborating closely with data scientists
  • Strong leadership skills, with 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 cross-functional environments
  • Passion for learning and staying current with evolving technologies and industry trend

Nice to haves

  • 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 reduces wildfires, protects earth’s natural resources and helps solve our climate crisis.
  • Flexible working environment with a lot of autonomy. We build our work days around our lives, not the other way around.
  • Other benefits like a remote working budget, an educational budget and time to develop new skills.
  • To be surrounded by an excellent, vibrant, smart team who have each other's back and believe in a culture of openness, tolerance and respect.
  • Equity and a competitive salary.

About our team

We are a group of 100 people from all over the world. Fifteen nationalities are represented in our team. We work remotely from eleven different countries and we are looking for candidates that are also living and working in one of these countries: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Denmark, Switzerland, and Canada. We meet up once a year in-person for our unforgettable team gathering event. We also offer the option to occasionally meet up for in-person collaboration.

Diversity & Inclusion

We place enormous value on diversity and inclusion and strive to continually bring in people of all genders, races, creeds, ethnicities, abilities and backgrounds. We believe that the best ideas emerge when people with different perspectives and approaches work together on a problem.

We’re always looking to diversify our team further, but we’re proud of the fact that four out of the nine people on our leadership team are female, 46% of the overall team are female and 20% of the team are people of color. Our team speaks fifteen languages: English, Dutch, French, Spanish, German, Italian, Portuguese, Russian, Luxembourgish, Lithuanian, Bulgarian, Cantonese, Estonian, Danish and Korean.

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.

_________________________________

Use of AI in Our Hiring Process

We sometimes use AI tools to support parts of our hiring process, such as helping us manage applications more efficiently or ensuring job descriptions are clear and inclusive. But don’t worry, all hiring decisions are always made by people, not machines. Any data processed by AI is handled securely in line with GDPR and our Privacy Notice.

Skills

PythonMachine LearningGDPR

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