Senior/ Staff Research Engineer

JR United Kingdom; City Of London; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

A leading company in AI drug discovery is seeking a Senior/Staff AI Research Engineer in London. The role involves developing cutting-edge AI models and scaling their performance on GPUs. Candidates should possess strong experience in AI/ML model deployment and proficiency in relevant programming languages.

Benefits

Access to professional growth via conferences

Inclusive, collaborative culture focused on innovation

Qualifications

• 5+ years of experience deploying AI/ML models in production settings.
• Skilled in distributed training (e.g., DDP, FSDP).
• Experience with GPU architectures and cloud platforms.

Responsibilities

• Develop AI models for drug discovery using deep learning frameworks.
• Scale and optimize distributed training of large AI models on GPUs.
• Communicate findings through documentation and presentations.

Skills

Python

C++

Deep Learning

AI/ML Model Deployment

Model Performance Optimization

Education

Bachelor's or Master's or PhD in Computer Science

Degree in Engineering or related field

Tools

PyTorch

JAX

Job description

Social network you want to login/join with:

Senior/ Staff Research Engineer, london (city of london)

col-narrow-left

Client:

GCS

Location:

london (city of london), United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

col-narrow-right

Job Views:

3

Posted:

16.06.2025

Expiry Date:

31.07.2025

col-wide

Job Description:

? Senior/Staff AI Research Engineer

? Location: London (Hybrid)

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

Key Responsibilities

• 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

• 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!