At a Glance
- Tasks: Develop deep-learning pipelines and enhance model usability for groundbreaking research.
- Company: Leading research organisation in London focused on innovative machine learning.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and career advancement.
- Why this job: Join a pioneering team and contribute to cutting-edge research in drug discovery.
- Qualifications: Relevant degree and experience in machine learning, Python, and scientific software.
The predicted salary is between 50000 - 70000 € per year.
We are currently looking for a Machine Learning Engineer to join a leading research organisation based in London. As Machine Learning Engineer, you will be responsible for advancing data-processing, model-building, and deployment capabilities for a pioneering research organisation.
KEY DUTIES AND RESPONSIBILITIES:
- Develop deep-learning pipelines for nuclear magnetic resonance (NMR) data and innovative machine learning approaches to elucidate and quantify interactions between small molecules and intrinsically disordered proteins.
- Enhance the usability of built models by implementing automated, streamlined, and efficient software solutions in line with best practices, and build model-deployment and job-launching systems for internal and external use.
- Collaborate closely with other computational and NMR team members, in addition to experimental biophysicists, assisting with experimental data handling and curation, and mentoring the interdisciplinary team in machine-learning and data analysis methods.
- Stay current with breakthroughs in machine learning, neural networks, NMR, and computational technologies, contributing to the design and execution of cutting-edge machine learning and NMR research projects.
ROLE REQUIREMENTS:
- Relevant degree in a technical field with proven experience in machine learning or model-building.
- Proven industry experience in applying machine learning and modelling techniques to graph-based data such as molecules and proteins, as well as time series. An ability to demonstrate innovative ways of working (for example work on disordered proteins and consideration of the next frontier in drug discovery) will be highly advantageous.
- A working knowledge and practical experience with Python, and extensive experience with the scientific and machine-learning stack: Numpy, Torch/Tensorflow/Jax, Scikit-learn, Polars, SQL.
Hyper Recruitment Solutions Ltd (HRS) is an Equal Opportunities employer. We welcome applications from anyone who meets the role requirements. HRS exclusively supports the Life Science sectors, combining recruitment expertise with scientific knowledge to help you advance your career.
Machine Learning Engineer employer: Hyper Recruitment Solutions LTD
Join a pioneering research organisation in London as a Machine Learning Engineer, where you will be at the forefront of innovative scientific advancements. Our collaborative work culture fosters creativity and growth, offering ample opportunities for professional development and mentorship within an interdisciplinary team. Enjoy the unique advantage of contributing to cutting-edge research in drug discovery while working in a vibrant city known for its rich academic and cultural environment.
Contact Detail:
Hyper Recruitment Solutions LTD Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to professionals in the machine learning field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving deep learning and NMR data. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python and machine learning frameworks like TensorFlow or PyTorch.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting roles waiting for talented Machine Learning Engineers like you. Plus, it’s a great way to get noticed by our team.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with deep-learning pipelines and any relevant projects you've worked on, especially those involving NMR data or innovative machine learning approaches.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Include specific examples of how you've applied Python and other tools like TensorFlow or Scikit-learn in real-world scenarios. This will help us see your practical experience in action.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background aligns with our research goals. Be sure to mention any collaborative experiences you've had with interdisciplinary teams.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Hyper Recruitment Solutions LTD
✨Know Your Tech Stack
Make sure you’re well-versed in the specific tools mentioned in the job description, like Python, Numpy, and TensorFlow. Brush up on your knowledge of these technologies and be ready to discuss how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in machine learning or model-building. Think of examples where you had to innovate or adapt your approach, especially in relation to graph-based data or disordered proteins.
✨Collaborate and Communicate
Since collaboration is key in this role, be ready to discuss how you’ve worked with interdisciplinary teams in the past. Highlight any mentoring experiences and how you’ve helped others understand complex machine-learning concepts.
✨Stay Current with Trends
Research recent breakthroughs in machine learning and NMR technologies. Being able to discuss current trends and how they might apply to the role will show your passion and commitment to staying at the forefront of the field.
