At a Glance
- Tasks: Build scalable ML and physics infrastructure for drug discovery with cutting-edge technology.
- Company: Lila Sciences, a leader in innovative drug discovery solutions.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative team atmosphere in the vibrant city of Cambridge.
- Why this job: Make a real impact in healthcare by turning research into robust systems.
- Qualifications: Strong Python skills, experience with ML frameworks, and knowledge of Docker and Kubernetes.
The predicted salary is between 45000 - 55000 £ per year.
Lila Sciences is seeking a Research Engineer to bridge research and production, building scalable ML and physics infrastructure for drug discovery. You will collaborate with scientists to turn prototypes into robust, distributed systems across compute environments in Cambridge.
You should have strong Python software engineering skills, experience with ML frameworks (PyTorch, JAX), and hands-on work with Docker, Kubernetes, and GPU workflows.
#J-18808-LjbffrResearch Engineer: Scalable ML & Physics Infrastructure in Cambridge employer: Lilasciences
At Lila Sciences, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Senior Principal or Principal Software Engineer in our AI Lab Execution System team, you will have the opportunity to lead cutting-edge projects that directly impact scientific discovery while enjoying comprehensive benefits, flexible time off, and a commitment to employee growth through mentorship and educational assistance. Join us in a dynamic environment where your contributions will shape the future of AI in science, all while working alongside passionate professionals dedicated to solving humanity's greatest challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer: Scalable ML & Physics Infrastructure in Cambridge
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Research Engineer: Scalable ML & Physics Infrastructure in Cambridge
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Lilasciences, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Lilasciences. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Lilasciences
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Lilasciences!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
