At a Glance
- Tasks: Develop and deploy machine learning solutions for drug discovery and molecular design.
- Company: Innovative AI-driven drug discovery company with a strong customer base.
- Benefits: Competitive salary, collaborative environment, and opportunities for impactful work.
- Other info: Dynamic role with excellent career growth and the chance to work on real-world problems.
- Why this job: Join a multidisciplinary team and contribute to groundbreaking advancements in healthcare.
- Qualifications: Experience in machine learning systems and strong coding skills required.
The predicted salary is between 50000 - 70000 £ per year.
CT19 is partnering with an innovative AI-driven drug discovery company that is building advanced machine learning solutions for drug discovery. Having established a strong customer base across biotech and pharma, they are now looking to hire a Research Engineer to help scale its machine learning capabilities and contribute to the next generation of computational drug discovery tools. This is an opportunity to join a highly technical, multidisciplinary team working at the intersection of machine learning, chemistry, biology and software engineering. You'll play a key role in developing production-grade ML systems, supporting scientific innovation, and helping deliver impactful solutions used by researchers worldwide.
The role: As a Research Engineer, you will be responsible for developing and deploying machine learning solutions that support molecular design and drug discovery workflows. You will work closely with scientists, engineers and end users to transform cutting-edge research into robust, scalable products.
Key Responsibilities:- Develop and optimise machine learning models for molecular property prediction and related scientific applications
- Expand and maintain automated model development and evaluation workflows
- Build and improve ML infrastructure, including training pipelines, experiment tracking, model registries and deployment processes
- Curate, validate and prepare scientific datasets for model development
- Collaborate with cross-functional teams to design and deliver user-focused solutions
- Contribute to technical documentation, publications and presentations where appropriate
- Support the ongoing evolution of engineering standards, tooling and best practices
- Commercial experience building and deploying machine learning systems in production environments
- Strong software engineering fundamentals and coding skills
- Experience with MLOps tooling, experiment tracking, model serving and containerisation technologies
- Exposure to cloud platforms such as AWS, GCP or Azure
- Familiarity with infrastructure-as-code approaches and modern development workflows
- Strong communication skills with the ability to collaborate across technical and scientific disciplines
- Experience working with molecular, chemical or biological datasets
- Exposure to computational chemistry, cheminformatics or drug discovery applications
- Contributions to open-source scientific or machine learning software projects
- PhD or advanced degree in Chemistry, Computational Chemistry, Computer Science, Machine Learning or a related discipline
Reach out to mason@ct-19.co.uk for more information!
Machine Learning Engineer - AI Drug Discovery employer: CT19
CT19 is an exceptional employer, offering a dynamic work environment where innovation thrives at the intersection of machine learning and drug discovery. With a strong focus on employee growth, you will have the opportunity to collaborate with a multidisciplinary team, contributing to impactful solutions that advance scientific research globally. The company fosters a culture of collaboration and continuous learning, making it an ideal place for those passionate about making a difference in the biotech and pharma sectors.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - AI Drug Discovery
✨Tip Number 1
Network like a pro! Connect with professionals in the AI and drug discovery fields on LinkedIn. Join relevant groups, attend webinars, and don’t hesitate to reach out for informational chats. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to molecular design or drug discovery. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and ML concepts. Practice common algorithms and data structures, and be ready to discuss your past projects in detail. We recommend using platforms like LeetCode or HackerRank for practice.
✨Tip Number 4
Don’t just apply anywhere—apply through our website! Tailor your application to highlight your experience with MLOps and cloud platforms. Make sure to emphasise your collaborative skills, as teamwork is key in this multidisciplinary role.
We think you need these skills to ace Machine Learning Engineer - AI Drug Discovery
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning systems and software engineering. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI in drug discovery and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills:When detailing your experience, focus on specific tools and technologies you've used, especially those related to MLOps, cloud platforms, and model deployment. We’re keen to know how you’ve tackled challenges in previous roles!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture!
How to prepare for a job interview at CT19
✨Know Your ML Models Inside Out
Make sure you can discuss the machine learning models you've worked with in detail. Be prepared to explain how you developed and optimised them, especially in the context of molecular property prediction. This shows your technical depth and readiness for the role.
✨Showcase Your Collaboration Skills
Since this role involves working closely with scientists and engineers, be ready to share examples of how you've successfully collaborated in multidisciplinary teams. Highlight any projects where you transformed research into practical solutions, as this will resonate well with the interviewers.
✨Familiarise Yourself with MLOps Tools
Brush up on your knowledge of MLOps tooling and practices. Be prepared to discuss your experience with experiment tracking, model serving, and containerisation technologies. Showing that you're comfortable with these tools will demonstrate your readiness to contribute to their ML infrastructure.
✨Prepare Questions About Their Work
Have a few thoughtful questions ready about the company's current projects or challenges they face in drug discovery. This not only shows your genuine interest in the role but also gives you insight into how you can make an impact if you join their team.
