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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, hands-on experience, and opportunities to influence technical direction.
- Why this job: Make a real impact in synthetic genomics while working with cutting-edge ML technologies.
- Qualifications: Background in engineering and experience with ML tools like PyTorch and Hugging Face.
- Other info: Dynamic environment with opportunities for growth and collaboration with experimental biologists.
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 in Cambridge 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 in Cambridge
✨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, especially those involving PyTorch and Hugging Face. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your experience with ML technologies and how you've collaborated with others in past projects. We want to see your problem-solving skills in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace On-site ML Research Engineer Genomics & Bioengineering in Cambridge
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 candidates 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, be prepared to discuss past experiences where you’ve successfully collaborated with others. Highlight any projects where teamwork led to innovative solutions, as this will demonstrate your ability to 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.
✨Ask Insightful Questions
At the end of the interview, don’t shy away from asking questions about the company’s current projects or future directions in synthetic genomics. This shows your enthusiasm for the role and helps you gauge if the company aligns with your career goals.