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Engineering Manager, Machine Learning

Overstory · Remote, US + Canada, EU

Publicada em 18 de dez. de 2024

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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. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description. 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

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