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- Tasks: Join a dynamic team to develop AI solutions for drug discovery.
- Company: Be part of an innovative biotech start-up revolutionising healthcare with cutting-edge technology.
- Benefits: Enjoy a competitive salary, equity options, flexible work arrangements, and comprehensive health benefits.
- Why this job: Make a real impact in biotech while working with advanced machine learning technologies.
- Qualifications: Strong Python skills, experience in LLM development, and a background in biology or drug discovery required.
- Other info: Work 3 days onsite and 2 days remotely for a balanced lifestyle.
The predicted salary is between 96000 - 224000 £ per year.
Our client, an exciting Biotech start-up is seeking Senior Machine Learning Engineers for their latest product in AI Drug Discovery. You must have experience in Biology, preference being within Drug Discovery.
Requirements:
- Strong proficiency in Python
- Experience with LLM development
- Experience in deploying ML models at scale
- Understanding of NLP
- Proven track record in productionizing ML models
Benefits:
- Salary up to £160,000
- Equity/share scheme
- 3 days onsite, 2 days remote
- Private medical insurance
- Wellness cash plan
- Company pension scheme
Apply now with your updated CV - rheywood@ndctek.com
Contact Detail:
Seer Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer - Biotech
✨Tip Number 1
Make sure to showcase your experience in Biology and Drug Discovery during any networking opportunities. Engage with professionals in the biotech field on platforms like LinkedIn, and discuss your relevant projects to highlight your expertise.
✨Tip Number 2
Attend industry conferences or webinars focused on AI in Drug Discovery. This will not only expand your knowledge but also help you connect with potential employers and peers who can provide insights into the hiring process.
✨Tip Number 3
Join online communities or forums related to Machine Learning and Biotech. Engaging in discussions and sharing your insights can help you build a reputation in the field, making you a more attractive candidate for the role.
✨Tip Number 4
Prepare to discuss specific examples of how you've deployed ML models at scale. Be ready to explain your thought process and the impact of your work, as this will demonstrate your practical experience and problem-solving skills to potential employers.
We think you need these skills to ace Senior ML Engineer - Biotech
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Machine Learning and Biology, particularly in Drug Discovery. Use specific examples of projects you've worked on that demonstrate your proficiency in Python and LLM development.
Craft a Compelling Cover Letter: Write a cover letter that explains why you're passionate about AI in Drug Discovery. Mention your understanding of NLP and how your previous work has prepared you for this role. Be sure to connect your skills directly to the job requirements.
Showcase Your Projects: If applicable, include links to any relevant projects or publications that showcase your ability to deploy ML models at scale. This could be GitHub repositories or research papers that highlight your contributions to the field.
Proofread and Format: Before submitting your application, carefully proofread your documents for any errors. Ensure that your CV and cover letter are well-formatted and easy to read, as this reflects your attention to detail.
How to prepare for a job interview at Seer
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and any relevant projects you've worked on. Highlight your experience with LLM development and deploying ML models at scale, as these are crucial for the role.
✨Demonstrate Your Understanding of Drug Discovery
Since the position is within AI Drug Discovery, make sure to articulate your knowledge of biology and how it relates to drug discovery processes. This will show that you understand the industry and can contribute effectively.
✨Prepare for NLP Questions
Given the emphasis on NLP, brush up on your understanding of natural language processing techniques. Be ready to discuss how you've applied NLP in previous projects and the impact it had on the outcomes.
✨Discuss Productionisation Experience
Have examples ready that demonstrate your proven track record in productionising ML models. Discuss challenges you faced and how you overcame them, as this will showcase your problem-solving skills and practical experience.
