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- Tasks: Build and implement scalable ML platforms on Google Cloud, deploying AI models into production.
- Company: Join a leading firm in Financial Services driving AI innovation for growth and scalability.
- Benefits: Enjoy flexible work options, competitive salary, and opportunities for professional development.
- Why this job: Be part of an agile team, shaping the future of AI in a dynamic industry with real impact.
- Qualifications: 5+ years in Machine Learning, strong GCP skills, and experience with model migration and deployment.
- Other info: Ideal for those passionate about AI and looking to make a difference in financial services.
The predicted salary is between 43200 - 72000 £ 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
Familiarise yourself with Google Cloud Platform (GCP) and its services, especially Vertex AI and BigQuery. Consider taking online courses or certifications to deepen your understanding, as this will not only boost your confidence but also demonstrate your commitment to the role.
✨Tip Number 2
Network with professionals in the Financial Services and Insurance sector. Attend industry meetups or webinars where you can connect with current employees or leaders in the field. This could provide valuable insights into the company culture and expectations.
✨Tip Number 3
Showcase your hands-on experience with migrating models from Dataiku or similar platforms to GCP. Prepare specific examples of past projects where you've successfully implemented ML solutions, as this will help you stand out during interviews.
✨Tip Number 4
Stay updated on the latest trends in machine learning and AI, particularly in the context of financial services. Being knowledgeable about recent advancements can help you engage in meaningful discussions during interviews and demonstrate your passion for the field.
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, machine learning frameworks, and any relevant projects. Use keywords from the job description to demonstrate that you meet the specific requirements.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about AI innovation in the Financial Services sector. Mention your experience with migrating models and building ML platforms, and how you can contribute to the company's goals.
Showcase Relevant Projects: If you have worked on projects involving GCP, Dataiku, or similar tools, include them in your application. Describe your role, the technologies used, and the impact of your work to give a clear picture of your capabilities.
Highlight Collaboration Skills: Since the role involves working in an agile environment with cross-functional teams, emphasise your teamwork and collaboration skills. Provide examples of how you've successfully worked with data scientists, engineers, and other stakeholders in past roles.
How to prepare for a job interview at Eden Smith Group
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Google Cloud Platform, especially Vertex AI and BigQuery. Highlight specific projects where you've built or deployed ML models, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Your Problem-Solving Skills
Expect to encounter scenario-based questions that assess your ability to architect scalable ML solutions. Think of examples from your past work where you had to design end-to-end ML pipelines or migrate models, and articulate your thought process clearly.
✨Understand the Business Context
Since this role is within the Financial Services and Insurance sector, it’s crucial to understand how AI can drive innovation in these fields. Research current trends and challenges in the industry, and be ready to discuss how your skills can contribute to their goals.
✨Prepare for Collaborative Discussions
As you'll be working in an agile squad, be ready to talk about your experience collaborating with cross-functional teams. Share examples of how you’ve worked with data scientists, software developers, and DevOps teams to achieve common objectives.
