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- Tasks: Innovate in machine learning for biological projects and build production systems.
- Company: Pioneering biotech startup in Cambridge with a focus on collaboration.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Dynamic team atmosphere where your ideas can shape the future of biotech.
- Why this job: Make a real impact in synthetic genomics while working with cutting-edge ML technologies.
- Qualifications: Background in engineering and hands-on experience with ML tools like PyTorch.
The predicted salary is between 50000 - 70000 £ per year.
A pioneering biotech startup in Cambridge is looking for an ML engineer to innovate in the area of machine learning applied to biological projects. This role involves building production systems and collaborating closely with experimental biologists to drive advancements in synthetic genomics.
The ideal candidate will have a background in engineering and hands-on experience with ML technologies like PyTorch and Hugging Face, and will thrive in a dynamic, collaborative environment where they can genuinely influence technical direction.
On-site ML Research Engineer Genomics & Bioengineering employer: Constructive Bio
Contact Detail:
Constructive Bio Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land On-site ML Research Engineer Genomics & Bioengineering
✨Tip Number 1
Network like a pro! Reach out to professionals in the biotech and ML fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show your passion for the industry.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with PyTorch and Hugging Face. This will give potential employers a taste of what you can do and how you can contribute to their innovative work.
✨Tip Number 3
Prepare for those interviews! Research the company and its projects, especially in synthetic genomics. Be ready to discuss how your background in engineering can help drive advancements in their work.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace On-site ML Research Engineer Genomics & Bioengineering
Some tips for your application 🫡
Show Your Passion for Biotech: When writing your application, let your enthusiasm for biotech and machine learning shine through. We want to see how your background aligns with our mission to innovate in synthetic genomics!
Highlight Relevant Experience: Make sure to showcase any hands-on experience you have with ML technologies like PyTorch and Hugging Face. We’re looking for someone who can hit the ground running, so don’t hold back on those details!
Collaborative Spirit is Key: Since this role involves working closely with experimental biologists, emphasise your teamwork skills. Share examples of how you've successfully collaborated in the past – we love a good team player!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Constructive Bio
✨Know Your Tech Inside Out
Make sure you’re well-versed in the ML technologies mentioned in the job description, like PyTorch and Hugging Face. Brush up on your knowledge of how these tools can be applied to biological projects, as this will show your genuine interest and expertise.
✨Showcase Your Collaborative Spirit
Since the role involves working closely with experimental biologists, prepare examples of past collaborations. Highlight how you’ve successfully worked in teams, tackled challenges together, and contributed to a shared goal. This will demonstrate that you can thrive in a dynamic environment.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and understanding of machine learning concepts. Practice explaining complex ideas clearly and concisely, as you may need to communicate your thought process to non-technical team members.
✨Research the Company’s Projects
Dive into the startup's current projects and innovations in synthetic genomics. Being able to discuss their work and how you can contribute will not only impress them but also show that you’re genuinely interested in their mission and vision.