We are looking for a Machine Learning Engineer or Research Engineer with expertise in deploying deep learning models, particularly transformer-based models like large language models. The role involves enhancing the performance of an existing machine learning system (including fine-tuning the underlying models) through various improvements across the system. Strong analytical and machine learning capabilities are essential for success in this position.
We are looking for someone who can demonstrate that they can be self-directed in the role and be the team’s top expert in their area.
We value ambition to learn and execute beyond just years of experience.
We are located in London, one of the world’s foremost financial and tech hubs.
We accept applications from people from any background and are striving to create a diverse and inclusive work environment.
About the role
We are building the next generation of interfaces in how capital allocators use AI to interact with the world of sustainability data, like how ChatGPT showed a different way to think about search. Our end-to-end data pipeline enables investors to engage in the climate transition through financial instruments more easily and faster than ever.
The team has built a productised version from our proof-of-concept and are looking to continue developing our machine learning capability and enable new workflows for our users. We are looking for a candidate with a background in large language models to take ownership of the machine learning system performance through engineering modifications, prompt engineering, fine-tuning and by creating a system of models to enable the utilisation of the new generation of models in actual workflows. The role will be yours to shape with the chance to make a big positive impact on the company and on the world.
This is a hybrid position – You’ll be expected to be in the office at least 3 days a week.
As a Research Engineer / MLE at ClimateAligned, you’d get to be responsible for:
Implementing machine learning systems in a variety of environments, particularly in the cloud.
Integrating established research into high-value and high-impact applied projects.
Performing applied research to use machine learning (particularly deep learning, transfer learning and few-shot learning) in real world problems.
Collaborating with Software Engineers to build end-to-end working analytics code, including designing and evaluating new ideas (prototyping) as well as making simple solutions work for customers.
Reporting and presenting results and findings clearly and efficiently, both internally and externally.
In practice, your job for the first months in the role will involve:
Familiarising yourself with the current state and performance of our machine learning system in our product implementation together with the technical team.
Taking ownership of the areas of improvement that can be gained in the machine learning system and looking to implement some of the first gains from the list.
Working with the rest of the team to integrate your model & system improvements into our production analytical core.
Stretch target: Fine-tune one of the newest open-source language models with our data and deploy to test it in our systems.
As we embark on this journey, we are looking for people with the ability to deliver great work and to be best-in-class in their specialism. We do not expect you to be an expert in every task from the beginning as we work in the intersection of several disciplines, but we do expect to see enthusiasm to learn and persistence in finding great solutions to challenging problems.
As the ideal future teammate, you have:
Proven knowledge of machine learning and/or statistics and demonstrable ability to apply to complex unstructured data
Competency in Python and familiarity with other programming languages such as C++ or Java
Experience with implementing numerical methods and data visualisation
Good knowledge of algorithm design, evaluation and implementation
Experience with deep learning frameworks (e.g. Torch, TensorFlow)
Ability to adopt an innovative approach to thinking about data in new and creative ways
Hands on experience of communicating results and findings clearly and efficiently across different levels of audience understanding
At least a Masters in machine learning, computer science, mathematics, physics, electrical engineering, or equivalent
Even better if you can bring some of the following:
Previous experience in Natural Language Processing with large language models
Experience with GPU programming
Previous experience leading your own machine learning projects within academia and/or private sector
PhD in machine learning, computer science, mathematics, physics, electrical engineering, or equivalent
Working knowledge of source control management such as Git and issue management systems such as GitLab or JIRA.
Familiarity with AWS, GCP or Azure
Compensation & Benefits
In addition to a great team and an exciting mission, we will offer you:
Employee stock options
25 days of annual leave + Bank Holidays
Flexibility with working from home (3 days in, 2 days flexible)
Snacks & coffee at the office
Private healthcare (including dental and vision checks)
We’re predominantly looking for candidates with the right to work in the UK. Exceptional candidates may qualify for VISA sponsorship.
Applications will be reviewed on a rolling basis. We can’t wait to hear from you!
How to Apply
Please send an email to firstname.lastname@example.org with the following information:
The role you are applying for
Your name and how to get in touch with you
Cover letter / brief message on why you would like to join us
Link to your LinkedIn page, website or anything else you think might be relevant (unless already mentioned in your CV)