ML Engineer

AI for drug design is limited by sparse and fragmented data. deepmirror is an AI-native drug design platform built around curated, non-public experimental molecule property measurements (potency, binding, ADMET) aggregated from patents, papers, and partners. We help chemistry teams choose the next best experiments to progress programs faster with fewer dead ends. Since launching in 2023, our platform is now used by hundreds of chemists across the globe to impact real world drug programs in oncology, dementia, infammation, and global health. Now, we are looking for an experienced ML engineer to supercharge our product.

In this role, you will design and develop cutting-edge algorithms for drug design to tackle real-world challenges of AI in drug discovery. This is an outstanding opportunity for someone who wants to be involved from day one of the start-up journey and who wants to put new processes into place to build a powerful platform in a high-performing and collaborative team, based in beautiful Victoria House in the heart of London.

As part of the platform team, you will build and contribute to core services integrating advanced molecular property prediction algorithms into our platform and interface with users to improve their experience. Leveraging your expertise in ML engineering, we encourage you to seize the opportunity to be independent and drive innovation and quality. In the role, you will have substantial growth opportunities, allowing you to shape deepmirror’s technological framework from its inception and learn in an interdisciplinary environment at the interface of physics, chemistry, biology, and machine learning.

Should I apply?

We want to be upfront about what it is like to work at deepmirror and thought hard about the principles that guide our work. Before you apply, let's dive into how our values influence the way we work as a team and ensure they resonate with you.

We Persevere:

We believe that great work comes from dedication, continuous learning, and pushing boundaries. We trust you to manage your time in a way that helps you develop your skills while contributing to impactful projects. If you thrive on learning and enjoy challenging yourself, you'll fit right in.

We Care

We love what we do and deeply care about our product, customers, and colleagues. We thrive as a collaborative team where everyone is willing to go the extra mile for our customers. We create an environment where asking for support and extending a helping hand are equally valued. Be part of something big and contribute to a culture of support, customer focus, and shared ambition.

We Own

Nobody will dictate how you do things, but you will be held accountable for the impact of your work, as we value outcomes over outputs. If you thrive in an environment where you take responsibility, solve problems proactively, and drive your own success, you will do well here.

At deepmirror, you will challenge yourself, be supported, and be given the freedom to excel. Join a team where striving, caring, and ownership are not just values but a way of life. If this resonates with you, deepmirror could be your next big adventure—read on for the 'boring' bits.

You Will:

• Build predictive ML models for molecular property prediction, foundation models, and Auto ML pipelines.
• Build ML infrastructure including training pipelines, experiment tracking, model registry, CI/CD for models.
• Production model serving with a focus on low-latency inference.
• Data pipelines that prepare, validate, and version datasets for training and evaluation.
• Close collaboration with product and customers to ship user-facing features

Requirements

• 3+ years of industry experience building and deploying ML systems in production (not just research prototypes).
• Strong software engineering skills.
• Hands-on experience with MLOps tooling experiment tracking and model serving, and containerisation.
• Comfort with cloud infrastructure (AWS, GCP, or Azure) and infrastructure-as-code.
• Strong communication skills and ability to work across disciplines.

Nice to Have:

• Experience deploying ML models into production environments.
• Contributions to open-source scientific software (e.g., RDKit, OpenMM, PyTorch or related tools).
• PhD in chemistry, computational chemistry, or a related physical science / computer science.

If you meet at least 60% of the requirements or nice-to-have qualifications, we encourage you to apply.

Benefits

• Competitive Option Plan in line with the stage of the company
• Frequent social events and off-sites
• Private medical insurance
• 1-week remote working per quarter
• Cycle to Work Scheme
• Pension Scheme: 5%/5% employer/employee