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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 working, and comprehensive health benefits.
- Why this job: Make a real impact in biotech while working with advanced machine learning technologies.
- Qualifications: Strong Python skills, LLM development experience, 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.
Senior ML Engineer - Biotech employer: Seer
Contact Detail:
Seer Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer - Biotech
✨Tip Number 1
Network with professionals in the biotech and AI fields. Attend industry conferences or webinars where you can meet people who work in drug discovery and machine learning. This can help you gain insights into the latest trends and potentially lead to referrals.
✨Tip Number 2
Showcase your projects related to ML and drug discovery on platforms like GitHub. Having a portfolio that demonstrates your experience with Python, LLM development, and deploying ML models will make you stand out to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of NLP and productionising ML models. Be ready to discuss specific challenges you've faced in previous roles and how you overcame them, as this will demonstrate your problem-solving skills.
✨Tip Number 4
Research the company thoroughly before your interview. Understand their products, mission, and the specific role of AI in their drug discovery process. This will allow you to tailor your responses and show genuine interest in their work.
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, particularly in the context of Biotech and Drug Discovery. Emphasise your proficiency in Python and any relevant projects involving LLM development.
Showcase Relevant Experience: In your application, detail your experience with deploying ML models at scale and your understanding of NLP. Provide specific examples of how you've productionised ML models in previous roles.
Craft a Compelling Cover Letter: Write a cover letter that connects your background in Biology and Machine Learning to the role. Explain why you're excited about the opportunity to work in AI Drug Discovery and how you can contribute to the start-up's success.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail and professionalism.
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. Share examples of how you've applied machine learning in this context.
✨Prepare for NLP Questions
Given the requirement for an understanding of NLP, brush up on key concepts and be ready to discuss any relevant experience you have. Consider discussing specific NLP techniques you've used in past projects.
✨Discuss Productionizing ML Models
Have concrete examples ready that demonstrate your proven track record in productionizing ML models. Be prepared to explain the challenges you faced and how you overcame them, as this will show your problem-solving skills.
