At a Glance
- Tasks: Build and maintain ML infrastructure, deploy AI applications, and improve workflows.
- Company: Leading global alternative investment manager with a tech-driven approach.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Join a cutting-edge team and make a real impact in the AI space.
- Qualifications: 4+ years in software or infrastructure, strong Python/Java skills, and Kubernetes knowledge.
The predicted salary is between 60000 - 80000 £ per year.
Our client is a leading global alternative investment manager with over $80bn AUM. Technology sits at the core of their investment process, with a long history of building proprietary systematic trading and research platforms. They are seeking a Senior MLOps Engineer to join a growing AI Platform team. You'll be responsible for building and operating the infrastructure, tooling, and services that support ML and LLM applications across the firm, helping move models from research into production at scale.
Key Responsibilities
- Build, deploy, and maintain ML/LLM infrastructure on Kubernetes.
- Develop and support internal APIs, platform services, and data products.
- Productionise AI applications with a focus on scalability, reliability, and observability.
- Improve CI/CD, automation, and deployment workflows for ML systems.
- Partner with engineers, researchers, and business teams to deliver AI solutions.
- Drive best practices across MLOps, platform engineering, and model operations.
Requirements
- 4+ years' experience building and operating production software or infrastructure.
- Strong Python and/or Java development skills.
- Experience deploying and supporting ML or LLM workloads in production.
- Deep knowledge of Kubernetes, containers, and cloud-native systems.
- Background in data engineering, ML infrastructure, or platform engineering.
- Strong communication skills and experience working with technical and non-technical stakeholders.
Machine Learning Engineer in London employer: Acquire Me
As a leading global alternative investment manager, our client offers an exceptional work environment for Machine Learning Engineers, where technology is at the forefront of their innovative investment strategies. Employees benefit from a collaborative culture that fosters professional growth and development, alongside competitive compensation and comprehensive benefits. With a focus on cutting-edge AI applications and a commitment to best practices in MLOps, this role provides a unique opportunity to make a significant impact within a dynamic and forward-thinking team.
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We think this is how you could land Machine Learning Engineer in London
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We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
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