MLOps Engineer — Production ML for Drug Discovery

Excelity; Greater London; On-site; GBP 80,000 - 100,000; Full time

Job summary

A cutting-edge AI company in Greater London is looking for an MLOps Engineer who will focus on deploying and operating large-scale machine learning models. The successful candidate will optimize performance, work closely with ML researchers, and ensure advanced models function efficiently across distributed systems. Ideal applicants have strong experience with PyTorch and ML infrastructure, are comfortable with model lifecycle management, and are inspired by making a significant real-world impact in scientific applications. A highly competitive salary and equity ownership are offered.

Benefits

Opportunity for real-world impact

Talented team collaboration

Significant ownership in projects

Highly competitive salary with equity

Qualifications

• Strong experience deploying and operating machine learning models in production environments.
• Proven ability to optimize training and inference workloads, including profiling performance.
• Comfortable collaborating closely with ML researchers to translate research models into production.

Responsibilities

• Optimize, deploy, and operate large-scale machine learning models for Boltz Lab.
• Ensure advanced models run efficiently across distributed systems.
• Work closely with ML researchers to turn trained models into production-ready services.

Skills

Deploying and operating machine learning models

Optimizing training and inference workloads

Hands-on experience with PyTorch

Understanding of MLOps best practices

Strong software engineering fundamentals

Collaboration with ML researchers

Job description

A cutting-edge AI company in Greater London is looking for an MLOps Engineer who will focus on deploying and operating large-scale machine learning models. The successful candidate will optimize performance, work closely with ML researchers, and ensure advanced models function efficiently across distributed systems. Ideal applicants have strong experience with PyTorch and ML infrastructure, are comfortable with model lifecycle management, and are inspired by making a significant real-world impact in scientific applications. A highly competitive salary and equity ownership are offered.