ML Research Engineer (Contract)

Location: Remote (UK-based) with a weekly in-person collaboration in London.

Contract Type: Fixed-term contract, 3-4 months.

Salary: £52,000 per annum (pro rata for the contract term).

Applications deadline: Please note that this job post will close on Friday at 10:00 PM. Ensure your application is submitted before this time.

Application requirements: Please confirm your right to work in the UK for the duration of the 3–4 month contract. Visa sponsorship is not available for this role.

Aeris-UK is an applied AI company working on real-world problems that require creativity, rigour and solid engineering. We build machine learning systems that are efficient, understandable and ready to operate in the complexity of real environments, whether that involves supporting infrastructure resilience, enabling autonomous decision-making or developing tools to help people reason under uncertainty. Our projects are practical in focus but intellectually demanding, drawing on ideas from simulation, human-AI interaction, multi-agent learning and model-based reasoning. We are a small team with a strong research culture and a shared interest in solving meaningful and challenging problems. Everyone contributes directly to project work, and we collaborate across disciplines, whether your background is in machine learning, data analytics, reinforcement learning, software engineering, probabilistic modelling, simulation or systems design. We often work in partnership with researchers, government teams and other specialists, so communication and openness are important in everything we do.

We are seeking a highly skilled and motivated ML Research Engineer to join our dynamic team for 3-4 months to work on specific projects. In this role, you will be responsible for building and optimizing complex simulation environments to facilitate the training of machine learning models. The ideal candidate will have a background in programming, modelling and machine learning, with optional expertise in reinforcement learning and/or simulation.

As a team, we value clarity over hierarchy and experimentation over perfection. We are growing steadily and carefully, with a mix of longer-term research and near-term applications. For someone early in their career, this offers exposure to a broad range of ideas, the chance to work across technical boundaries and the opportunity to influence how we grow.

What You’ll Be Doing

• Developing and implementing complex simulation environments to support machine learning model training.
• Collaborating with clients and stakeholders to understand requirements and design simulation scenarios aligned with real-world applications.
• Applying expertise in modelling to create realistic and scalable simulations.
• Carrying out data science activities, including data exploration and analysis, to inform simulation design and model training strategies.
• Designing and implementing machine learning models, with a focus on both supervised and unsupervised learning techniques.
• Exploring and implementing reinforcement learning algorithms, with a preference for experience in multi-agent environments.
• Developing and integrating physics or engineering models into simulation environments to enhance realism and accuracy.
• Applying your strong software skills, including proficiency in Python and ideally another programming language.
• Applying DevOps processes to ensure seamless integration of ML training pipeline.

Who We’re Looking For

• Bachelor’s or higher degree in Computer Science, Machine Learning or any related field.
• Proven experience in programming with Python and familiarity with at least one additional programming language.
• Demonstrated experience in simulation and machine learning.
• Familiarity with or experience in agile project management methodologies.
• Strong understanding of data science principles, including data exploration and analysis.
• Proficiency in developing and implementing machine learning models, both supervised and unsupervised.
• Familiarity with model development, such as physics or engineering models, for integration into simulations.
• Good software development and debugging skills.
• DevOps expertise/experience for efficient integration and deployment.
• Optional: Experience in reinforcement learning (especially in multi-agent environments) or signal processing would be advantageous.

What We Can Offer You

The Aeris team comes from different personal, professional and organisational backgrounds. We are driven by a deep intellectual curiosity that powers us forward each day. You’ll learn something new from people you meet and also have the opportunity to make your mark on a growing start-up.

Some of our benefits:

• Flexible working: We believe people have different responsibilities and interests that require something different to a strict working day. We trust our people to organize for their own work.
• Remote working but with the opportunity to work together weekly (if in London).

If you are passionate about pushing the boundaries of machine learning research and have the skills to contribute to our innovative projects, we invite you to apply and join our forward-thinking team.