Senior ML Engineer, Foundation Models | Remote & Equity in Southampton

Senior ML Engineer, Foundation Models | Remote & Equity in Southampton

Southampton Full-Time 80000 - 100000 Β£ / year (est.) No working from home possible
Cross Border Talents

At a Glance

  • Tasks: Lead the development and optimisation of next-gen foundation models in AI.
  • Company: Cross Border Talents, a forward-thinking tech company with a hybrid work culture.
  • Benefits: Remote work flexibility, equity options, and competitive salary.
  • Other info: Opportunity for career growth and collaboration with founders.
  • Why this job: Join a team solving cutting-edge engineering challenges in production-scale AI.
  • Qualifications: Experience in machine learning and large-scale system architecture.

The predicted salary is between 80000 - 100000 Β£ per year.

Cross Border Talents seeks a Senior Machine Learning Engineer (Foundation Models) to lead development, optimization, and production deployment of a next-generation foundation model in a hybrid London setup with monthly office visits. You will architect large-scale ML systems, optimize distributed training and inference, and work directly with founders to solve cutting-edge engineering challenges in production-scale AI.

Senior ML Engineer, Foundation Models | Remote & Equity in Southampton employer: Cross Border Talents

Cross Border Talents is an exceptional employer, offering a dynamic work environment in the vibrant city of Bristol, where innovation meets real-world application. Employees benefit from a collaborative culture that fosters professional growth and development, alongside opportunities to work on cutting-edge technology in autonomous robotics. With a focus on practical solutions and a commitment to employee well-being, this role promises meaningful contributions to the future of AI and robotics.

Cross Border Talents

Contact Details:

Cross Border Talents Recruitment Team

We think you need these skills to ace Senior ML Engineer, Foundation Models | Remote & Equity in Southampton

Machine Learning
Foundation Models
Large-Scale ML Systems Architecture
Distributed Training Optimization
Inference Optimization
Production Deployment
Engineering Problem-Solving