Software Engineer

London, Hybrid - 4 Day Work Week

£65,000 - 75,000 per year

About us

Climate Policy Radar is a non-profit organisation building open databases and research tools so people can discover and understand complex information, in particular long-text documents, on climate, nature and development. Our data and tools help governments, researchers, international organisations, civil society, and the private sector to understand and advance effective climate policies and deploy climate finance. Harnessing data science and AI, and pioneering the application of natural language processing to this domain, our work renders previously unstructured, siloed data more readable and accessible.

We are a team of ~30 technologists and climate policy experts who care a lot about the ‘how’ (our values and culture) as well as the ‘what’. As part of that, we have embraced a flexible, hybrid approach to work, including a 4 day work week.

We are looking for a Software Engineer to join our data science team.

Roles and responsibilities

This is a growth hire, adding a software engineer to Climate Policy Radar's data science team. Reporting to the Head of Data Science, you'll be a fully integrated member of our team. You're the person who will turn a promising prototype into something real - deploying models, automating pipelines, and building the infrastructure that connects us to other engineering teams.

You'll pair frequently with data scientists to understand their needs, and work across API development, cloud infrastructure, front-end demos, and automation. A lot of the team's best ideas are currently bottlenecked by our engineering capacity; this role exists to unlock them.

About the data science team

Climate Policy Radar's engineering org is split into a few functional teams: programmes (domain experts), platform (high-quality data sharing), application (user-facing tools), and data science (models and evaluation). Despite those splits, most of our work is cross-functional.

The data science team builds the models that power our search engine, classifiers, and LLM workflows, and the evaluation frameworks that keep them honest. Our work directly informs policy decisions, so we care a lot about evaluation, monitoring, and minimising bias. We're research-informed but production-focused, and we default to working in the open by publishing datasets, models, and papers wherever we can. We also share what we've learned through blogs, papers, and public talks.

Tech preferences

The vast majority of the data science team's work is written in Python, so we'll expect you to be a fluent reader/writer!

In addition, here's an (unordered) list of tools which we work with regularly. We're always open to new suggestions of tools you've had success with, but familiarity with these tools will help you integrate with our existing stack:

• ML & NLP: PyTorch, Huggingface Transformers, Pydantic AI, Pandas, Spacy
• APIs & backend: Python, FastAPI, Pydantic
• Data & infrastructure: DuckDB, Snowflake, PostgreSQL, Docker, AWS (ECS, S3, etc.), Pulumi, Prefect, GitHub Actions
• Search: Vespa
• Testing, evaluation & monitoring: Pytest, Hypothesis, Weights & Biases, Posthog

What will you be working on?

Climate Policy Radar's core product is a search engine for 30,000+ climate policy documents, powered by ML models and classifiers developed by our data science team. The team has three major strands of work planned for 2026:

1. Working on our search engine to improving information retrieval
2. Working on classifiers to create more connections between our core data
3. Building workflows with LLMs which are able to synthesise disconnected pieces of evidence into a coherent answer

Your engineering expertise will unlock progress across all three strands. Over the next year, you're likely to:

• Work closely with the other engineering teams to help shape our research & development priorities
• Deploy LLM agent workflows that data scientists have developed, taking them from notebook prototypes to production services
• Build and deploy front-end demos (using Streamlit or similar) that illustrate new features and help stakeholders understand what's possible

You bring with you:

To hit the ground running in this role, we anticipate that you'll have the following:

Nice to haves

In addition to the above, we'd love to hear from you if you've got experience with any/all of these:

• MLOps or experience deploying machine learning models to production
• Working with LLMs and agent frameworks (we like Pydantic AI, but we're open to others)
• Infrastructure-as-code tools like Pulumi, Terraform, or CloudFormation
• Workflow orchestration tools like Prefect, Airflow, or similar Working with search engines or vector databases for information retrieval (Vespa, Elasticsearch, etc)
• Building data pipelines or ETL systems
• Developing around the Wikidata / Wikibase / Wikimedia ecosystem
• Working with knowledge graphs, or graph databases (Neo4j, etc)
• Experience working in research-focused or cross-disciplinary teams

We are looking for candidates with significant experience in highly collaborative cross-functional teams, excitement about working in a startup/scaleup environment and all that brings.

We are a mission driven organisation, and work best with people who have strong alignment with our values . We care about them deeply.

Salary and Benefits:

• A deep commitment to employee wellbeing, including policies such as 4 day workweek (same pay, Fridays off), unlimited annual leave, and a wellbeing allowance
• A vibrant, collaborative, empathetic work culture that thrives on innovation and the impact of our work
• Hybrid work environment (2 days a week) in London. We welcome conversations about flexibility and remote work to accommodate individual needs

Interview process

We know that applying for a new job can be full of uncertainties - and we aim to reduce those by communicating clearly. Our process is made of several stages (see below). After each stage, we’ll contact you as soon as we can and no longer than 2 working days, to let you know if you will be progressing to the next stage.

If you have a disability or special need that requires accommodation during the process of application and selection, please let us know.

Process:

1. 30-60 minute screening call with our recruiter
2. 60 minute remote behavioural interview with two team members, focusing on communication and culture fit
3. Task: 2-3 hour take-home task (scheduled to be sent and returned at a time that suits you)
4. 60 minute interview to discuss your task
5. 30 minute in-person final fit interview with CEO and Head of People
6. Offer subject to reference

We’ve all felt the anxiety of waiting to hear back from interviews, so we will contact you no later than 2 working days after each interview to let you know if you will be progressing.

Right to Work in the UK

Unfortunately, we are currently unable to sponsor work visas. Only applicants legally authorised to work in the UK will be considered.

Equal opportunities

At Climate Policy Radar, We are committed to fostering a workplace that is inclusive and equitable. Climate Policy Radar welcomes applicants from all backgrounds and does not tolerate discrimination in any aspect of employment. We actively work to ensure equal opportunities for all, regardless of heritage, ancestry, national origin, citizenship, religion, sex, sexual orientation, gender identity, age, disability, relationship choices, or criminal history, in line with legal requirements. We also consider qualified applicants regardless of criminal histories, in line with legal requirements.

Not sure if you tick all the boxes but feel like you align with our values, are excited about working in Climate Change and AI and have the potential to do well in the role? Click apply! We’d love to hear from you.