Engineering Manager, Machine Learning

About the role

The ML Engineering Manager position at Overstory is a unique opportunity to lead a team of machine learning engineers and data scientists. This role involves enabling these teams to deliver high-quality ML-driven capabilities, supporting the development of products using satellite imagery and geospatial datasets, and fostering a collaborative and inclusive work environment.

Responsibilities

• 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

Requirements

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 trends

Qualifications

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)

Skills

• Technical Depth in Machine Learning, Data Systems, or Applied ML
• Leadership Skills
• Communication Skills
• Collaboration Skills
• Technical Decision-Making

Benefits

Competitive, location-specific compensation and benefits

A flexible, autonomous, and collaborative working environment rooted in trust

Home office stipend, coworking, and ongoing education budgets

Pay

Location-specific compensation

Schedule

Flexible schedule

Company Culture

A culture that genuinely embodies each of our core values

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. 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.