Senior/ Staff Research Engineer

JR United Kingdom; London; On-site; GBP 70,000 - 120,000; Full time

Job summary

A leading company in AI drug discovery is seeking an experienced professional to develop and optimize advanced AI models. The role involves scaling distributed training on GPUs and contributing to impactful research in healthcare. Candidates with strong backgrounds in Python, C++, and deep learning frameworks are encouraged to apply.

Benefits

Access to professional growth via conferences and workshops

Inclusive and collaborative culture focused on innovation

Qualifications

• 5+ years of experience deploying AI/ML models in production settings.
• Experience with GPU architectures and cloud platforms.
• Familiarity with low-level hardware tuning and custom CUDA kernel development.

Responsibilities

• Develop 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 training and inference.

Skills

Python

C++

Deep Learning

Distributed Training

Model Optimization

Education

Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field

Tools

PyTorch

Jax

CUDA

Job description

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Are you excited to drive AI drug discovery forward by scaling SOTA models and optimizing neural nets on GPUs?

Qualifications

1. Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field
2. 5+ years of experience deploying AI/ML models in production settings
3. Proficient in Python, C++, and deep learning frameworks like PyTorch or Jax
4. Skilled in distributed training (e.g., DDP, FSDP) and model performance optimization
5. Experience with GPU architectures, cloud platforms, and hardware tradeoffs
6. Familiarity with low-level hardware tuning and custom CUDA kernel development

Key Responsibilities

1. Develop cutting-edge AI models for drug discovery using deep learning frameworks
2. Scale and optimize distributed training of large AI models on GPUs
3. Enhance performance of AI models during both training and inference stages
4. Communicate findings through documentation, presentations, and stay updated on AI advancements
5. Contribute to impactful research at the AI-healthcare frontier
6. Access to professional growth via conferences, workshops, and training
7. Work within an 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!