Engineering Manager, Machine Learning

Overstory; San Diego (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Overstory is seeking an ML Engineering Manager to lead cross-functional teams of up to 10 ML engineers and data scientists. You will guide technical direction and delivery while collaborating with product, design, and engineering leaders.

You will help attract and grow ML talent, foster an inclusive culture, and ensure strategic alignment with product goals. Hands-on coding is limited, but deep technical input is valued when needed.

Qualifications

• 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 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 ML, data systems, or applied ML to guide teams.
• Experience working with Python-based ML or data workflows and collaborating with data scientists.
• Strong leadership skills with a coaching mindset and 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 trends.

Responsibilities

• Enable cross-functional teams to deliver high-quality ML-driven capabilities across product areas.
• Support teams working with satellite imagery and geospatial datasets, balancing experimentation and iteration.
• Grow the teams by attracting and hiring great Data and ML talent.
• Foster an inclusive, supportive culture where everyone can do their best work.
• Provide regular coaching and feedback to help others thrive and reach aspirations.
• Partner with Product Managers to balance short- and long-term goals.
• Ensure technical approaches support future product and modelling needs.
• Collaborate with other Product, Design and Engineering leaders on strategy, technology, and people.
• Evolve Data and ML practices and introduce ways of working that improve collaboration, delivery, and learning.

Skills

ML leadership

Climate tech

Startup experience

Product-minded

ML/data systems depth

Python ML workflows

Communication

Cross-functional collaboration

Learning mindset

Job description

Role & Team

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’ll 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

Skills & Experience

• 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 Have

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

Note: We believe that all people are capable of great things.

What We Offer

• Competitive, location-specific compensation and benefits

• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around

• Home office stipend, coworking and ongoing education budgets

• A company culture that genuinely embodies each of our core values

• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis