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Technical Product Manager - ML Platform

Amsterdam, Noord-Holland, NetherlandsEngineering

Job description

We are Dexter Energy! We are an Amsterdam-based scale-up that’s using AI-based forecasting and optimization services in order to help renewable energy companies solve this problem. Our mission is to enable a sustainable and affordable power system that changes the energy market. We truly believe we can make a significant impact on climate change. Our software makes renewables more predictable and profitable, helping push fossil fuels out of the market, and speeding up the energy transition.

Power up our team

The Engineering Department at Dexter Energy is where the magic happens. Our team of talented engineers works tirelessly to create AI software that predicts and optimizes renewable energy solutions.

In this new and impactful role, you will be teaming up with the team Machine Learning Platform, the tech wizards who breathe life into our AI, making it smarter and more efficient every day: Juman, Joost, Brian, Fedor, Remmert - our Software and Data Engineers, and Olivia, Engineering Manager. You will report directly to Mehmet, our CTO, and will work towards delivering an exceptional ML Platform product.

This role is the watt you've been looking for!

As a Technical Product Manager - ML Platform at Dexter Energy, you will be responsible for building a common infrastructure (ML Platform) that all Machine Learning products at Dexter will operate on. Your primary focus will be to drive the vision, strategy, and execution of our ML Platform to ensure it meets the evolving needs of internal customers - Dexter’s product teams. There are plans for this platform to have external users in the future.

You will collaborate closely with cross-functional teams, including product and engineering teams, to deliver the best ML Platform experience in our industry and maximize the customer value. You will partner closely with the Engineering Manager of the ML Platform team - in terms of execution and joint responsibility in building the roadmap.

Major areas of responsibility include:

  • Roadmap Ownership: Develop and maintain a comprehensive roadmap for the ML Platform, including the identification of requirements and use cases. Ensure that the roadmap aligns with the company's overall product strategy and objectives.

  • Stakeholder Engagement: Collaborate with internal stakeholders to gather feedback, insights, and requirements related to the ML Platform. Act as a central point of contact for stakeholders and facilitate productive discussions to drive the platform's development

  • Prioritization and Planning: Work closely with the ML Platform team to prioritize features, enhancements, and projects. Communicate and align on priorities, ensuring that the roadmap reflects the most critical business needs and internal customer requirements.

  • Alignment Building: Proactively build alignment and trust with internal customers (product teams). Understand their needs and work towards aligning the ML Platform's development efforts with their goals. Initiate discussions and workshops to ensure a shared understanding of priorities.

  • Collaboration with Engineering Manager: Partner with the Engineering Manager of the ML Platform team to define goals, deliverables, and project timelines. Collaborate on technical aspects and ensure that the platform's development aligns with engineering capabilities and constraints.

  • Requirements Gathering: Continuously surface and document requirements and use cases for the ML Platform. Leverage these insights to make informed decisions about feature development and improvements.

  • Communication: Effectively communicate the ML Platform's roadmap, progress, and key updates to internal stakeholders, ensuring that they are well-informed about the platform's development status. Maintain open lines of communication with teams and individuals affected by the platform's changes.

  • Performance Monitoring: Oversee the performance of the ML Platform, including metrics related to usage, efficiency, and reliability.

  • Cross-functional Collaboration: Foster collaboration between different teams within the organization, such as engineering and product, to ensure the successful development and integration of machine learning solutions.

  • Documentation: Make sure that there is a comprehensive documentation for the ML Platform, including guides and integration examples, to facilitate seamless usage and integration by internal and external users.

It’s time to amp up your career

What’s in it for you?

  • Most of our work is truly greenfield. Of course, we have live products, but we expect that for the upcoming 2 to 3 years we’ll be building features and services from the ground up

  • You’ll be part of setting up the fundamentals for future growth. Together with your team, you will work on establishing the baseline for future development

  • A healthy environment, where we put trust in our fellow Dexterians. With this trust comes flexibility to do your job how you see fit and in our setting, there’s plenty of room for your ideas and wishes

  • We’re also improving our “extras package” for Learning and Development, working from home equipment and so on

  • You will be surrounded by extremely smart people (our Backend Engineer João really wanted this in)

Job requirements

Energize us with these qualifications:

To be successful in this role, you'll need:

  • Product Management Experience: A minimum of 3 years of experience as a Product Manager or Product Owner, with a focus on building products which are internal platforms. This experience should emphasize the ability to conceptualize and deliver new solutions and features, rather than managing technical debt. This role will initially focus on building internal tooling but with a vision to go external in the future.

  • ML Platform Expertise: Ideally, prior experience in building ML Platforms or similar data-driven platforms. Alternatively, experience in non-ML Platforms with a strong background in the machine learning domain, demonstrating an understanding of the unique challenges and requirements in this field.

  • Feasibility Assessment: Ability to review and validate the feasibility of ML projects, including making go/no-go decisions based on technical and business factors. This involves assessing the viability of proposed solutions and providing informed input on whether projects should proceed.

  • Familiarity with Domain Driven Design (DDD) principles and practices.

  • Technical Background: A technical background, such as previous experience as a software engineer, is preferred but not mandatory. Such a background can aid in understanding technical solutions, analyzing data, and effectively communicating with engineering teams.

  • Excellent Communication: Strong communication and stakeholder management skills, as the role involves collaborating with cross-functional teams, including data scientists, engineers, and business stakeholders.

  • Passion for the Domain: A genuine passion for machine learning and data engineering, and a desire to make a positive impact in the ML and data-driven technology space.

See our Stackshare to learn more about the technologies we use.

Are you ready to supercharge your career and join a company that's pushing the boundaries of clean energy technology? Then we want to hear from you!

Apply now!

Dexter Energy is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.