Machine Learning Engineer (remote role)

Role Overview:

Want to solve unique, large scale, highly complex technical problems that improve outcomes for nature? Pivotal is seeking an experienced Machine Learning Engineer to play a crucial role in the development of solutions that scale machine learning to the next level. It will be high visibility and impactful in building and scaling our data & analytics platform. Join us in providing the data people and companies need to invest in positive outcomes for nature!

Responsibilities:

• Design, build and evaluate acoustic and computer vision algorithms and models suitable for use in our species identification pipelines.
• Train, tune and debug production models, inform decisions on how to collect and synthesise training data.
• Create data pipelines and MLOps frameworks that deliver high-efficiency ML-simulation solutions with minimal friction, supporting deployments across IoT, and cloud environments (Azure, AWS).
• Partner with product leads to develop and implement the technical vision and strategy, ensuring alignment of the ML strategy with Pivotal’s mission & commercialisation timelines.
  
• Influence the development of the technical design and architecture of the stack.
• Cultivate a culture of collaboration, impact, innovation, and health.

You should apply if you have:

• Bachelor’s degree or higher in Machine Learning, Computational Engineering, or another related technical field.
• Minimum of 3-5 years hands-on ML development experience, creating and implementing computer vision and/or acoustics models.
• Experience delivering in a commercial environment, and ideally experience working in startups.
• A highly analytical and technical mindset, with experience in solving complex production problems to take research to production.
• Excellent communication skills and a people sensibility which enables you to work in a cross-functionally in roadmap planning, stakeholder management, requirements gathering and alignment with peers towards milestones and deliverables.
• An entrepreneurial mindset and passion for building and growing a successful company, and the ability to work in a fast-paced, evolving environment.
• A desire to build ground-breaking technology to support the protection and restoration of the natural world.
  
• (Ideally) based in the UK or Western Europe.

About Pivotal:

We are a team of ecologists and technologists who believe good business must be good for nature. We are revolutionising the nature space by linking biodiversity commitments and actions to real, auditable data. Evidence of real improvements in biodiversity is critical to the expansion of innovative financial mechanisms which fund the restoration of nature. Without this evidence, investors are exposed to the risk of false promises, human bias and reputational damage.

Following our €5.6m seed round investment from some of Europe’s leading VCs and advocates for a better planet, we are growing our team to support our next stage of growth. We are here to build an institution that changes the way the world collaboratively works on one of the largest problems our planet is facing, and the only way we can do that is by bringing together a team who is passionate about restoring nature in new and exciting ways.

What we offer you:

• Impact; you will be joining us in the early days of the business giving you plenty of opportunities to contribute to developing an entirely new discipline that will change how value is unlocked from nature
• Industry competitive compensation and equity in the business
• Autonomy; we want to build a culture of trust & give you the space to do your best work
• A fun and diverse team of smart and very driven people
• A very competitive employee participation program
• Remote-first company

We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion or belief, sex, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity, disability status or any other basis as protected by applicable law.