At a Glance
- Tasks: Design and implement machine learning frameworks and solutions in a collaborative environment.
- Company: 1st Central is a leading insurance company focused on smart data and technology.
- Benefits: Enjoy flexible hybrid working, great perks, and a supportive workplace culture.
- Why this job: Join a winning team recognised as Insurance Employer of the Year and drive innovation in data science.
- Qualifications: Strong knowledge of Microsoft Azure, Python, and MLOps frameworks required.
- Other info: Remote work options available; perfect for tech-savvy individuals eager to make an impact.
The predicted salary is between 48000 - 84000 £ per year.
We’re 1st Central, a market-leading insurance company utilising smart data and technology at pace. Rapid growth has been based on giving our 1.4 million customers exactly what they want: great value insurance with an excellent service. And that’s the same for our colleagues too; we won Insurance Employer of the Year at the British Insurance Awards 2024 and our Glassdoor score is pretty mega too!
We’re big on data: it gives us the insights we need to give the right cover to the right customers at the right price. But it’s the people inside and outside our business that power us and were currently on the hunt for 2 experienced Senior Machine Learning Operation Engineers to join our Data Function.
You’ll play a significant role within our Data Function, working on the design and implementation of machine learning model engineering frameworks, solutions, and best practices. You’ll be technically proficient in machine learning and its applications; you’ll demonstrate an understanding of data management and show a keen interest in keeping up with industry trends. You’ll work closely with different teams such as Data Science, Data Engineering, Architecture, and Software Development to ensure efficient operation and use of Data Science models and will facilitate the full life cycle of machine learning models from data ingestion, model development, testing, validation, deployment, to monitoring and retraining of models within different environments.
If you’ve a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence.
This is a flexible hybrid working role with occasional visits to our offices, when required,in either Salford Quays, Manchester, Haywards Heath, West Sussex, or Guernsey.If you live further afield, we’ll accept applications for remote workers! We offer great flexibility in working patterns and a company-wide culture to be proud of.
Core skills were looking for to succeed in the role:
- A strong understanding of Microsoft Azure, (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory)
- Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc
- You’ll be skilled in application of MLOps frameworks within a production environment
- Excellent communication skills, both verbal and written
- Strong time management and organisation skills
- Ability to diagnose and troubleshoot problems quickly
- Excellent problem-solving and analytic skills
Powering the business with the right tools
What’s involved:
- You’ll contribute to the design and implementation of Machine Learning Engineering standards and frameworks.
- You’ll support model development, with an emphasis on auditability, versioning, and data security.
- You’ll implement automated data science model testing and validation.
- You’ll assist in the optimisation of deployed ML model scoring code in production services.
- You’ll assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions.
- You’ll use CI/CD pipelines, manage the deployment and version management of large numbers of data science models (Azure DevOps).
- You’ll support the implementation of Machine Learning Ops on cloud (Azure & Azure ML. Experience with Databricks is advantageous.)
- You’ll protect against model degradation and operational performance issues through the development and continual automated monitoring of model execution and model quality.
- You’ll manage automatic model retraining within a production environment.
- You’ll engage in group discussions on system design and architecture, sharing knowledge with the wider engineering community.
- You’ll collaborate closely with data scientists, data engineers, architects, and the software development team.
- You’ll liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and identify new areas for improvements.
- You’ll adhere to the Group Code of Conduct and Fitness and Propriety policies, Company Policies, Values, guidelines, and other relevant standards/ regulations at all times.
Experience & knowledge
- Experience in developing and maintaining production ML systems, including automatic model retraining and monitoring of production models
- Deploying Infrastructure as Code (IAC) across various environments such as dev, uat and prod
- Handling large volumes of data in various stages of the data pipeline, from ingestion to processing
- Proven experience with feature stores, using them for both offline model development and online production usage
- Building integrations between cloud-based systems using APIs, specifically within the Azure environment
- Practical knowledge of agile methodologies applied in a data science and machine learning environment
- Designing, implementing, and maintaining data software development lifecycles, with a focus on continuous integration and deployment (CI/CD)
- Demonstratable expertise in machine learning methodology, best practices, and frameworks
- Understanding of microservices architecture, RESTful API design, development, and integration
- Basic understanding of networking concepts within Azure
- Familiarity with Docker and Kubernetes is advantageous
- Experience within financial/insurance services industry is advantageous
- Experience with AzureML and Databricks is advantageous
Skills & Qualifications
- Strong understanding of Microsoft Azure, (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory)
- Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc.
- Skilled in application of MLOps frameworks within a production environment
- Excellent communication skills, both verbal and written
- Strong time management and organisation skills
- Ability to diagnose and troubleshoot problems quickly
- Excellent problem-solving and analytic skills
Behaviours
- Embrace, embed and incorporate the company values
- Self-motivated and enthusiastic
- An organised and proactive approach
- Strong stakeholder management
- Ability to work on own initiative and as part of a team
- A flexible approach and positive attitude
- Strives to drive business improvements to contribute to the success of the business
This is just the start. Imagine where you could end up! The journey’s yours…
What can we do for you?
People first. Always. We’re passionate about our colleagues and know the best people deserve an extraordinary working environment. We owe it to them so that’s what we offer. Our workplaces are energetic, inspirational, supportive. To get a taste of the advantages you’ll enjoy, take a look at all our perks in full here .
Intrigued? Our Talent team can tell you everything you need to know about what we want and what we’re offering, so feel free to get in touch.
#J-18808-Ljbffr
Senior Machine Learning Operations Engineer employer: First Central
Contact Detail:
First Central Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Operations Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, especially Microsoft Azure and its various services. Having hands-on experience or projects that showcase your proficiency in Azure ML, Data Factory, and other relevant tools will set you apart.
✨Tip Number 2
Engage with the data science community by participating in forums or attending meetups focused on MLOps and machine learning. This not only helps you stay updated on industry trends but also allows you to network with professionals who might provide insights or referrals.
✨Tip Number 3
Prepare to discuss your previous experiences with model deployment and monitoring during interviews. Be ready to share specific examples of how you've implemented CI/CD pipelines or automated model retraining, as these are crucial aspects of the role.
✨Tip Number 4
Showcase your problem-solving skills by preparing for technical assessments or case studies that may be part of the interview process. Practice explaining your thought process clearly, as communication is key in collaborating with cross-functional teams.
We think you need these skills to ace Senior Machine Learning Operations Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Microsoft Azure, MLOps frameworks, and data science coding. Use specific examples that demonstrate your skills in machine learning operations and how you've contributed to similar projects.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your background aligns with their needs, particularly your experience in developing production ML systems and your understanding of data management.
Showcase Relevant Projects: If you have worked on relevant projects, include them in your application. Describe your role, the technologies used (like Azure ML or TensorFlow), and the impact of your work. This will help illustrate your hands-on experience.
Highlight Soft Skills: Don't forget to mention your communication, problem-solving, and organisational skills. These are crucial for collaborating with different teams and stakeholders, as highlighted in the job description.
How to prepare for a job interview at First Central
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Microsoft Azure and MLOps frameworks in detail. Highlight specific projects where you've implemented machine learning models, focusing on the tools and techniques you used.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your analytical skills. Prepare examples of challenges you've faced in previous roles and how you diagnosed and resolved them, particularly in a production environment.
✨Communicate Effectively
Since excellent communication is key for this role, practice articulating complex technical concepts in simple terms. Be ready to explain your thought process during model development and how you collaborate with cross-functional teams.
✨Stay Updated on Industry Trends
Research the latest advancements in machine learning and data science, especially those relevant to the insurance industry. Being knowledgeable about current trends will demonstrate your passion and commitment to continuous learning.