Lead Machine Learning and AI Engineer
London
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NatureMetrics
NatureMetrics is the World-Leading provider of Biodiversity monitoring data, using eDNA surveys, metabarcoding & more. Book your demo today!As we continue to grow, we're looking for a highly skilled and experienced Lead Machine Learning (ML) and artificial intelligence (AI) Engineer to drive the development and deployment of our advanced ML and AI learning solutions. In this pivotal role, you'll combine hands-on technical leadership with strategic vision, to build innovative models and scalable infrastructure that tackle complex ecological and geospatial challenges. You'll be instrumental in shaping our ML and AI roadmap, directly contributing to helping organisations understand and manage their impact on nature.
Key Responsibilities
Hands-on technical leadership: Lead the design, development and deployment of end-to-end ML and AI systems, from research and prototyping to productionisation and monitoring.
Model development: Lead the development and implementation of advanced ML algorithms and models to solve complex ecological and geospatial problems.
System design and architecture: Architect, build and maintain scalable, reliable, and efficient ML and AI pipelines and infrastructure.
Mentorship: Provide technical guidance, project management,and mentorship to a team of ML engineers and data scientists, fostering their growth and ensuring high-quality deliverables.
Product strategy and innovation: Collaborate with product managers and stakeholders to translate business requirements into technical solutions, contributing to the overall ML and AI strategy and identifying opportunities for innovation.We’re looking for a driven and collaborative technical leader 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:
- Significant experience in ML engineering or applied data science.
- A proven track record of successfully designing, building and deploying ML models into production environments at scale.
- Expertise in Python and relevant ML libraries.
- Strong 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.
- Experience working with bioinformatics, life sciences, or geospatial data.
- Strong understanding of software engineering best practices, including version control (e.g. Git), CI/CD, and testing.
- Strong understanding of MLOps principles and monitoring and evaluation tools.
- Experience of providing technical mentorship and guidance to junior ML engineers and data scientists.
- 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.
- Experience in a technical lead role.
- 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!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AI strategy Architecture BigQuery Bioinformatics CI/CD Deep Learning Engineering GCP Generative AI Git Google Cloud Machine Learning ML models MLOps Pipelines Prototyping Python PyTorch Reinforcement Learning Research TensorFlow Testing
Perks/benefits: Career development Competitive pay Flex hours
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