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- Tasks: Join an agile squad to build and extend a scalable ML platform on GCP.
- Company: Partnering with a leading organization in Financial Services, driving AI innovation.
- Benefits: Work remotely, enjoy corporate perks, and be part of a transformative AI journey.
- Why this job: Shape the future of AI in finance while collaborating with diverse teams in a dynamic environment.
- Qualifications: 5+ years in ML engineering, strong GCP expertise, and solid Python programming skills required.
- Other info: Experience in Financial Services is a plus; familiarity with GenAI models is desirable.
The predicted salary is between 54000 - 84000 £ per year.
About the Company:
We are partnering with a leading organisation in the Financial Services and Insurance sector, focused on driving AI innovation to support growth and scalability. As part of their AI transformation, we are seeking Senior Machine Learning Engineers to help architect and implement a scalable ML platform on Google Cloud Platform (GCP) and migrate existing models from Dataiku into the GCP ecosystem.
Role Overview:
As a Senior Machine Learning Engineer, you will work within an agile squad alongside data scientists, data engineers, software developers, and DevOps teams. Your primary focus will be on building and extending the ML platform, deploying AI models into production, and ensuring robust model monitoring and governance.
Key Responsibilities:
- Architect, design, and implement an ML platform on GCP to support scalable AI solutions.
- Migrate existing machine learning models from Dataiku (or similar platforms) into GCP.
- Develop end-to-end ML pipelines using GCP services such as Vertex AI, AI Platform, and BigQuery.
- Deploy AI models (both GenAI and non-GenAI) into production, ensuring scalability and security.
- Implement model monitoring frameworks to track data drift, concept drift, and overall performance.
- Establish and enforce standardised guardrails for model deployment, ensuring robust security and compliance.
- Collaborate with cross-functional teams in an agile environment, contributing to continuous improvement.
Skills & Experience Required:
- 5+ years of experience as a Machine Learning Engineer or similar role.
- Strong expertise in Google Cloud Platform, particularly Vertex AI, AI Platform, and BigQuery.
- Proven experience building and deploying ML platforms and AI models in production environments.
- Hands-on experience migrating models from Dataiku or similar tools into cloud platforms.
- Familiarity with GenAI models and open-source AI frameworks.
- Solid programming skills in Python, with experience in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Understanding of ML model monitoring, including data drift and concept drift detection.
- Knowledge of containerisation technologies (Docker) and orchestration tools (Kubernetes).
- Experience in the Financial Services or Insurance industry is highly desirable.
Senior Machine Learning Engineer employer: Eden Smith Group
Contact Detail:
Eden Smith Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience with Google Cloud Platform, especially with Vertex AI and BigQuery. Highlight any specific projects where you've built or deployed ML platforms, as this will demonstrate your hands-on expertise.
✨Tip Number 2
If you have experience migrating models from Dataiku or similar tools, be ready to discuss the challenges you faced and how you overcame them. This will show your problem-solving skills and adaptability in a cloud environment.
✨Tip Number 3
Familiarize yourself with the latest trends in GenAI models and open-source AI frameworks. Being able to discuss these topics during your interview can set you apart as a candidate who is not only experienced but also forward-thinking.
✨Tip Number 4
Since collaboration is key in this role, think of examples where you've successfully worked in cross-functional teams. Be prepared to share how you contributed to agile projects and what impact your contributions had on the overall success.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Google Cloud Platform, particularly Vertex AI and BigQuery. Include specific projects where you've built or deployed ML platforms, and mention any relevant experience in the Financial Services or Insurance industry.
Craft a Strong Cover Letter: In your cover letter, emphasize your hands-on experience with migrating models from Dataiku to GCP. Discuss your approach to building scalable ML solutions and how you ensure model monitoring and governance.
Showcase Relevant Projects: Include a section in your application that showcases specific projects or achievements related to machine learning and cloud platforms. Highlight any experience with GenAI models and your programming skills in Python.
Prepare for Technical Questions: Be ready to discuss your technical expertise during the interview process. Prepare to explain your experience with ML pipelines, model deployment, and monitoring frameworks, as well as your familiarity with containerization technologies like Docker.
How to prepare for a job interview at Eden Smith Group
✨Showcase Your GCP Expertise
Make sure to highlight your experience with Google Cloud Platform, especially with services like Vertex AI and BigQuery. Be prepared to discuss specific projects where you've implemented scalable ML solutions on GCP.
✨Demonstrate Your Migration Skills
Since migrating models from Dataiku is a key responsibility, come ready with examples of how you've successfully transitioned models to cloud platforms. Discuss the challenges you faced and how you overcame them.
✨Discuss Model Monitoring Strategies
Be prepared to talk about your understanding of model monitoring frameworks. Explain how you've tracked data drift and concept drift in previous roles, and why these practices are crucial for maintaining model performance.
✨Emphasize Collaboration in Agile Teams
As you'll be working in an agile squad, share experiences that demonstrate your ability to collaborate with cross-functional teams. Highlight any specific tools or methodologies you've used to enhance teamwork and continuous improvement.
