Lead Machine Learning and AI Engineer

NatureMetrics; London; On-site; GBP 150,000 - 200,000; Full time

Job summary

A leader in biodiversity monitoring is seeking a Lead Machine Learning Engineer in London to develop and deploy advanced ML and AI solutions. You will lead technical projects, mentor your team, and collaborate across functions. Ideal candidates have a strong background in ML engineering, Python, and cloud platforms, with a passion for impactful work in biodiversity. This position offers competitive salary and flexible working arrangements.

Benefits

Competitive Salary

Impactful work

Flexible work arrangements

Opportunities for professional growth

Benefits package including sustainability prioritization

Qualifications

• Significant experience in ML engineering or applied data science.
• Proven track record of designing, building and deploying ML models.
• Excellent communication and stakeholder management skills.

Responsibilities

• Lead design and deployment of ML and AI systems.
• Develop and implement advanced ML algorithms.
• Mentor a team of ML engineers.

Skills

ML engineering

Data science

Python

Deep learning frameworks (TensorFlow, PyTorch)

Cloud platforms (GCP, BigQuery)

MLOps principles

Stakeholder management

Bioinformatics or geospatial data

Job description

The role

NatureMetrics is a global leader in biodiversity monitoring and environmental DNA (eDNA) analysis, transforming the scale at which nature can be quantified. Our cutting-edge solutions enable organisations to monitor nature impact across sectors, from conservation to industry and inform sustainability decisions with unprecedented accuracy. With a strong market leading position, NatureMetrics has established a robust client base and developed a proprietary software platform that makes biodiversity insights accessible, actionable and scalable. As Earthshot Prize Finalists 2024, BloombergNEF Pioneers 2024, World Economic Forum Technology Pioneers 2024 and TechNation Future Fifty 2025 cohort members, we have the potential and the opportunity to change the way organisations operate.

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.

Why us?

At NatureMetrics diversity and inclusion are part of our DNA. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us to the communities we work with. Our values leave no space for stereotypes. We are all unique and pull together for a common purpose.

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!

About you

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.

Desirable but not required:

• Experience in a technical lead role.
• Experience working with software as a service (SaaS) products.

What's in it for you

• 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.