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For Companies At a Glance
- Tasks: Design and implement innovative AI/ML models for chemical data to accelerate scientific discovery.
- Company: Join Data Revival, a pioneering company transforming scientific data with AI.
- Benefits: Competitive salary, comprehensive benefits, and support for professional growth.
- Why this job: Make a real impact in science by building tools that empower researchers.
- Qualifications: Proficiency in Python and experience with deep learning frameworks like PyTorch.
- Other info: Collaborative team environment with opportunities for continuous learning.
The predicted salary is between 36000 - 60000 £ per year.
About Data Revival
We are on a mission to liberate scientific data. At Data Revival, 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.
Role Overview
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. In this role, you won’t just be tuning hyperparameters; you will own the architecture that extracts structure from chaos. You will work right at the core of our R&D team, taking 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.
Key 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 gut them and work with them past just 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 in Portsmouth employer: Data Revival
Contact Detail:
Data Revival Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI/ML and chemistry. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our mission at Data Revival. It’s a great way to get noticed and show your enthusiasm for the role.
We think you need these skills to ace AI/ML Engineer in Portsmouth
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. Share any relevant projects or experiences that highlight your passion!
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this specific role. Highlight your experience with Python, machine learning frameworks, and any relevant projects. We love seeing how your skills align with what we're looking for, so don’t hold back!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language and avoid jargon unless it's necessary. We appreciate a well-structured application that makes it easy for us to see your qualifications and fit for the role.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our mission at Data Revival!
How to prepare for a job interview at Data Revival
✨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 confidently will impress the interviewers. Make sure you can explain how your machine learning skills apply to chemical problems.
✨Showcase Your Projects
Prepare to talk about your past projects, especially those involving AI/ML in scientific contexts. Be ready to dive into the details of your architecture choices and the impact of your work. This is your chance to demonstrate ownership and innovation!
✨Familiarise with Tools and Frameworks
Since proficiency in Python and frameworks like PyTorch is crucial, make sure you're comfortable discussing your experience with these tools. Bring examples of how you've used them in previous roles or projects, particularly in relation to data pipelines and model development.
✨Stay Current with Trends
Research the latest advancements in machine learning and computational chemistry. Being able to discuss recent papers or breakthroughs shows your passion for the field and your commitment to staying updated, which is key for a role that bridges science and technology.
