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For Companies At a Glance
- Tasks: Design and implement innovative AI models to revolutionise chemical data understanding.
- Company: Join Data Revival, a pioneer in merging AI with scientific discovery.
- Benefits: Competitive salary, comprehensive benefits, and support for your professional growth.
- Why this job: Make a real impact on science by empowering researchers with advanced AI tools.
- Qualifications: Proficient in Python and experienced in machine learning frameworks like PyTorch.
- Other info: Collaborative team environment focused on cutting-edge research and continuous learning.
The predicted salary is between 36000 - 60000 £ per year.
Data Revival is on a mission to liberate scientific data. We bridge the gap between complex chemical knowledge and modern machine learning/AI. By building advanced AI tools, we turn static, vast chemical knowledge bases into accessible, searchable, and actionable insights for researchers pushing the boundaries of science.
We are looking for an AI/ML Engineer who is ready to tackle one of the hardest problems in science: teaching machines to understand chemistry. You will own the architecture that extracts structure from chaos and take novel models from a whiteboard concept to a production-ready tool that empowers scientists to discover new drugs and engineer next-generation materials. If you crave ownership and want to build technology that actually accelerates scientific discovery, this is your home.
Responsibilities
- Research, design, and implement novel machine learning architectures tailored for chemical and molecular data.
- Develop and maintain robust data pipelines for processing, augmenting, and featurising large-scale chemical datasets.
- Train, validate, and benchmark models to ensure they meet performance and accuracy requirements.
- Stay current with state-of-the-art research in machine learning, computational chemistry, and bioinformatics.
Required Skills & Experience
- Proficiency in Python and the core data science ecosystem (e.g., Pandas, NumPy, Scikit-learn).
- Hands-on experience with a modern deep learning framework, preferably PyTorch.
- Strong theoretical understanding of machine learning principles, including deep learning and classical statistical models.
- Knowledge of the inner workings of LLMs and VLMs, the ability to go beyond surface-level functionality.
- Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation.
- Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience.
Nice To Haves
- Prior experience in computational chemistry, bioinformatics, or cheminformatics.
- Experience with MLOps tools and practices for model serving and monitoring.
- Knowledge of tools like RDKit or other chemistry-specific data toolkits.
- Familiarity with containerisation of services (Docker/Kubernetes).
- Publications in relevant ML or scientific journals.
What We Offer
- Competitive salary and a comprehensive benefits package.
- The opportunity to work on cutting-edge research problems at the intersection of AI and chemistry.
- A key role in a small, collaborative team with direct impact on clients and product direction.
- Support for professional growth and continuous learning.
AI/ML Engineer - Data Revival in Southampton employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer - Data Revival in Southampton
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI/ML and chemistry fields on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and chemistry. Whether it's GitHub repos or a personal website, let us see your work in action. This is your chance to shine and demonstrate your expertise!
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML concepts. Practice coding challenges and review common algorithms. We recommend using platforms like LeetCode or HackerRank to get into the groove. Confidence is key when tackling those tricky questions!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our mission at Data Revival. So, hit that apply button and let’s get started!
We think you need these skills to ace AI/ML Engineer - Data Revival in Southampton
Some tips for your application 🫡
Show Your Passion for Chemistry: When you're writing your application, let your enthusiasm for chemistry and AI shine through. We want to see how you connect these fields and why you're excited about the role. A personal touch can make a big difference!
Highlight Relevant Experience: Make sure to showcase your experience with Python and machine learning frameworks like PyTorch. We’re looking for specific examples of projects or challenges you've tackled that relate to the responsibilities outlined in the job description.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the skills and experiences that align with our mission at Data Revival. This shows us that you’ve done your homework and are genuinely interested in joining our team.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it gives you a chance to explore more about us and what we do!
How to prepare for a job interview at Jobster
✨Know Your Chemistry
Brush up on your chemistry knowledge! Since the role involves teaching machines to understand chemical data, being able to discuss relevant concepts and how they relate to machine learning will impress the interviewers. Prepare to explain how your background in computational chemistry or related fields can contribute to their mission.
✨Showcase Your Technical Skills
Be ready to demonstrate your proficiency in Python and deep learning frameworks like PyTorch. Bring examples of past projects where you developed machine learning models or data pipelines. If you have experience with MLOps tools, make sure to highlight that too!
✨Stay Current with Trends
Familiarise yourself with the latest research in machine learning and computational chemistry. Being able to discuss recent advancements or papers shows your passion for the field and your commitment to continuous learning, which is something they value highly.
✨Prepare Questions
Interviews are a two-way street! Prepare thoughtful questions about their projects, team dynamics, and future goals. This not only shows your interest in the role but also helps you gauge if this is the right fit for you. Ask about their approach to model validation or how they handle data challenges in their work.
