Machine Learning Engineer (w/m/d)
3 Days Old
GX AI assistants are designed for Individual Investors, Credit and Claims professionals. Our assistants are being used right now in global financial institutions. Proven, trusted, non-hallucinating, our assistants are empowering financial professionals and delivering 10x improvements by supporting them in their day-to-day tasks.
Machine Learning Engineer, you will need to:
Develop a state of the art data science and ML runtime stack in a multi-cloud environment.
Lead on software engineering and software design for ML components.
Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity, and computer architecture.
Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created.
Build algorithms based on statistical modelling procedures and maintain scalable machine learning solutions in production.
Apply machine learning algorithms and libraries.
Research and implement best practices to improve the existing machine learning infrastructure.
Collaborate with data engineers, application programmers, and data scientists.
Qualification in a related field such as computer science, statistics, electrical engineering, mathematics, or physical sciences.
Strong computer programming skills, with knowledge of Python, R, and Java.
Experience scaling machine learning on data and compute grids.
Proficiency with Kubernetes, Docker, Linux, and cloud computing.
MLOps, CI, Git, and Agile processes.
Why you do not want to miss this career opportunity?
We are a mission-driven firm that is revolutionising the Insurance and Banking industry. Customer-centric organisation with innovation at the core of everything we do.
Capitalize on an unparalleled career progression opportunity.
Develop highly valued skills and build connections in the industry by working with top-tier Insurance and Banking clients on their mission-critical problems and deploying solutions integrated into their day-to-day workflows and processes.
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- Location:
- London
- Job Type:
- FullTime
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