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- Tasks: Develop cutting-edge AI models for drug discovery and optimise large-scale training on GPUs.
- Company: Join a pioneering company at the forefront of AI in healthcare.
- Benefits: Enjoy competitive salary, generous equity, private healthcare, and professional growth opportunities.
- Why this job: Be part of impactful research in a collaborative culture that values innovation and learning.
- Qualifications: Bachelor's/Master's/PhD in relevant fields with 5+ years of AI/ML experience required.
- Other info: Hybrid work model available; apply even if you meet 60-70% of the qualifications!
The predicted salary is between 120000 - 200000 £ per year.
Location: London (Hybrid)
Salary: £150-250k base + generous equity
Are you excited to drive AI drug discovery forward by scaling SOTA models and optimizing neural nets on GPUs?
Qualifications- Bachelor's/ Master's or PhD in Computer Science, Engineering, or a related field
- 5+ years of experience deploying AI/ML models in production settings
- Proficient in Python, C++, and deep learning frameworks like PyTorch or Jax
- Skilled in distributed training (e.g., DDP, FSDP) and model performance optimization
- Experience with GPU architectures, cloud platforms, and hardware tradeoffs
- Familiarity with low-level hardware tuning and custom CUDA kernel development
- Develop cutting-edge AI models for drug discovery using deep learning frameworks
- Scale and optimize distributed training of large AI models on GPUs
- Enhance performance of AI models during both training and inference stages
- Communicate findings through documentation, presentations, and stay updated on AI advancements
- Generous stock options
- Competitive base
- Private healthcare
- Generous pension contributions
- Contribute to impactful research at the AI-healthcare frontier
- Access to professional growth via conferences, workshops, and training
- Inclusive, collaborative culture focused on innovation and continuous learning
If you meet 60-70% of the requirements I would love to hear from you. Click the Easy Apply button!
Senior/ Staff Research Engineer (London Area) employer: GCS
Contact Detail:
GCS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior/ Staff Research Engineer (London Area)
✨Tip Number 1
Network with professionals in the AI and healthcare sectors. Attend industry conferences or local meetups to connect with people who work at companies like StudySmarter. This can help you gain insights into the role and potentially get a referral.
✨Tip Number 2
Showcase your projects related to AI drug discovery on platforms like GitHub. Having a portfolio that demonstrates your experience with deploying AI/ML models and optimising neural networks will make you stand out during the interview process.
✨Tip Number 3
Stay updated on the latest advancements in AI and deep learning frameworks. Follow relevant blogs, podcasts, and research papers to discuss these topics during interviews, showing your passion and commitment to the field.
✨Tip Number 4
Prepare to discuss your experience with distributed training and GPU optimisation in detail. Be ready to share specific examples of challenges you've faced and how you overcame them, as this will demonstrate your problem-solving skills and technical expertise.
We think you need these skills to ace Senior/ Staff Research Engineer (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI and machine learning, particularly any projects involving drug discovery. Use specific examples to demonstrate your proficiency in Python, C++, and deep learning frameworks.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI research and its application in healthcare. Mention how your background aligns with the job requirements and express your enthusiasm for contributing to impactful research.
Highlight Relevant Projects: In your application, include details about specific projects where you deployed AI/ML models in production settings. Emphasise your experience with distributed training and GPU optimisation, as these are key aspects of the role.
Showcase Continuous Learning: Mention any recent courses, workshops, or conferences you've attended related to AI and deep learning. This demonstrates your commitment to staying updated on advancements in the field, which is crucial for this position.
How to prepare for a job interview at GCS
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, C++, and deep learning frameworks like PyTorch or Jax. Bring examples of projects where you've deployed AI/ML models in production settings, as this will demonstrate your hands-on expertise.
✨Understand the Role's Impact
Research how AI is transforming drug discovery and be ready to discuss how your work can contribute to this field. Showing a genuine interest in the company's mission will set you apart from other candidates.
✨Prepare for Technical Questions
Expect questions on distributed training techniques and model performance optimisation. Brush up on concepts like DDP and FSDP, and be ready to explain how you've applied these in your previous roles.
✨Communicate Clearly
Since the role involves documenting findings and presenting results, practice explaining complex technical concepts in simple terms. This will showcase your ability to communicate effectively with both technical and non-technical stakeholders.
