ML Research Engineer in City of London

We are seeking a highly skilled, motivated and proactive ML Research Engineer to join our dynamic team. 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 strong background in programming, modelling and machine learning, with optional expertise in reinforcement learning.

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 reinforcement learning, software engineering, probabilistic modelling 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.

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 who wants breadth, ownership and exposure to challenging applied research, this offers the chance to work across technical boundaries and 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.
• Taking ownership of defined technical workstreams, breaking down ambiguous problems into practical next steps, and helping the team identify risks, blockers and opportunities.

Who we’re looking for:

• Master’s 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.
• Experience with DevOps practices for efficient integration and deployment.
• Optional: Experience in reinforcement learning, especially in multi-agent environments.
• Evidence of taking ownership of technical tasks or workstreams, proposing sensible next steps, and communicating risks, trade-offs and progress without needing close supervision.
• Comfortable working in a small team where engineers are expected to show initiative, lead on tasks when appropriate, and contribute ideas to project direction rather than waiting for fully specified instructions.

What we can offer you:

• 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).
• Generous pension: 8% employer salary contribution if employee pays at least 5% contribution; 5% employer contribution otherwise.
• Optional private health insurance.
• Eye tests and contribution towards cost of corrective lenses.
• Life insurance, critical illness protection (optional) and income protection.
• Social events: We have frequent socials and informal get-togethers to help make sure you enjoy your time with us.
• Professional memberships (with qualifying body).

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.