As we continue to grow, we're looking for a highly motivated and skilled Machine Learning (ML) and Artificial Intelligence (AI) Engineer to contribute to the development and deployment of our advanced ML and AI solutions. In this hands-on role, you'll be involved in building innovative models and scalable infrastructure that tackle complex ecological and geospatial challenges. You'll play a key part in our ML and AI roadmap, directly contributing to helping organisations understand and manage their impact on nature.
Key Responsibilities
Feature development: Lead on the design, development and deployment of end-to-end ML and AI features, from research and prototyping to productionisation and monitoring.
Model implementation: Implement advanced ML algorithms and models to solve complex ecological and geospatial problems.
System design: Contribute to the architecture, building and maintenance of scalable, reliable, and efficient ML and AI pipelines and infrastructure.
Product collaboration: Collaborate with product managers and stakeholders to translate business requirements into technical solutions, supporting the overall ML and AI strategy and identifying opportunities for innovation.We’re looking for a driven and collaborative engineer who is passionate about using ML and AI to make a tangible impact on helping organisations understand and manage their impact on nature. You should thrive in a dynamic, purpose-driven environment and be eager to tackle challenging, real-world problems.
You will bring:
- 2+ years of experience in ML engineering or applied data science.
- A proven track record of successfully contributing to the design, building and deployment of ML models into production environments.
- Expertise in Python and relevant ML libraries
- Experience with various ML algorithms (e.g. supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g. TensorFlow, PyTorch).
- Experience developing generative AI applications and deploying them into production.
- Experience working with cloud platforms, ideally Google Cloud Platform (GCP) and BigQuery.
- Proficiency in working with and querying global scale datasets.
- Familiarity working with bioinformatics, life sciences or geospatial data.
- Understanding of software engineering best practices, including version control (e.g. Git), CI/CD, and testing.
- Understanding of MLOps principles and monitoring and evaluation tools.
- Excellent communication and stakeholder management skills, with the ability to distil complex ideas for diverse audiences.
- A collaborative mindset and a desire to work cross-functionally across a purpose-driven business.
- Strong prior experience working with bioinformatics, life sciences or geospatial data in an ecological context.
- Experience working with software as a service (SaaS) products.
- Competitive Salary
- Impactful work with a purpose-driven team
- Flexible work arrangements
- Opportunities for professional growth
- Benefits package including salary sacrifice pension scheme prioritising sustainability; life assurance; Enhanced annual leave; Cycle to Work Scheme; enhanced family friendly policy.
We're a dynamic team passionate about nature and biodiversity and we take immense pride in our work and our impact. Join us on this journey!
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