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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 drug discovery are essential.
- 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
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 get 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 models will make you stand out to potential employers.
✨Tip Number 3
Stay updated on the latest advancements in NLP and ML technologies. Follow relevant blogs, podcasts, and research papers to ensure you can discuss current trends and innovations during interviews.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design questions specifically related to ML model deployment. Familiarise yourself with common tools and frameworks used in the industry to demonstrate your expertise.
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 any relevant experience you have with deploying ML models at scale and understanding NLP, as this will show your fit for the role.
Showcase Your Achievements: In your application, include quantifiable achievements related to productionizing ML models. This could be metrics from previous projects or successful implementations that had a significant impact.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. A polished application reflects attention to detail, which is crucial in a technical role like this.
How to prepare for a job interview at Seer
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and any relevant experience with LLM development. Bring examples of projects where you've successfully deployed ML models at scale, as this will demonstrate your technical capabilities.
✨Understand the Biotech Landscape
Familiarise yourself with the latest trends in AI Drug Discovery and how machine learning is being applied in the biotech sector. This knowledge will help you engage in meaningful discussions and show your genuine interest in the field.
✨Prepare for Behavioural Questions
Expect questions about your past experiences, particularly those that highlight your ability to work in teams and overcome challenges. Use the STAR method (Situation, Task, Action, Result) to structure your responses effectively.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's projects, culture, and future direction. This not only shows your enthusiasm but also helps you assess if the company aligns with your career goals.
