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- Tasks: Lead the development and deployment of a cutting-edge ML Ops platform.
- Company: Join a forward-thinking company focused on innovative data engineering solutions.
- Benefits: Enjoy hybrid working, generous leave, and exclusive discounts.
- Why this job: Be part of a dynamic team shaping the future of machine learning in a collaborative environment.
- Qualifications: Experience in ML Ops, Azure, Databricks, and strong problem-solving skills required.
- Other info: Flexible working hours and enhanced parental leave options available.
The predicted salary is between 43200 - 72000 £ per year.
The Machine Learning Operations Lead will be responsible for overseeing the development and deployment of the ML Ops platform for Project Pegasus. This role involves leading a cross-functional team to ensure the successful implementation and integration of ML models into the live pricing environment.
What you\’ll be responsible for:
- Lead the development and deployment of the ML Ops platform.
- Oversee the design, build, and testing of API services in the development environment.
- Ensure the platform supports offline analytics, ML models, lookup tables, and pricing actions.
- Collaborate with cross-functional teams to deliver the platform in an agile manner.
- Provide guidance on the implementation and management of Azure Cache (Redis), Postgres, Azure Redis, Databricks Delta Live tables, and Snowflake.
- Ensure the platform supports microservices and API-driven architecture with sub-2-second calls.
- Develop and maintain documentation, architecture diagrams, and other technical artifacts.
- Manage the integration of the platform with RADAR and other systems.
- Ensure code is production-ready and follow SDLC best practices.
- Proven experience in ML Ops engineering, with a focus on Azure and Databricks.
- Strong knowledge of Postgres, Azure Cache (Redis), and Azure Redis.
- Experience with Databricks Delta Live tables and Snowflake.
- Experience with Docker and Azure Container Services.
- Familiarity with API service development and orchestration.
- Experience in Data (Delta) Lake Architecture (Azure).
- Excellent problem-solving skills and ability to work collaboratively.
- Strong communication skills and ability to work with cross-functional teams.
- Experience with Azure Functions/Containers and Insights.
- Knowledge of integrating the platform with Snowflake for data storage and retrieval.
- Experience in managing the Software Development Life Cycle.
- Conducting peer-reviews and pair programming.
Additional benefits include:
- Hybrid working – 2 days in the office and 3 days working from home.
- 25 days annual leave, increasing to 27 days after 2 years and 30 days after 5 years, plus bank holidays.
- Discretionary annual bonus.
- Pension scheme – 5% employee, 6% employer.
- Flexible working arrangements and flexi-time.
- Healthcare Cash Plan for cashback on healthcare costs.
- Electric vehicle salary sacrifice scheme.
- Exclusive retailer discounts.
- Wellbeing, health & fitness app – Wrkit.
- Enhanced parental leave, including time off for IVF.
- Religious bank holidays, if applicable.
- Life Assurance – 4 times salary.
- Car and Travel Insurance Discounts.
- Cycle to Work Scheme.
- Employee Referral Scheme.
- Community support day.
About Somerset Bridge Group:
Somerset Bridge Group is dedicated to delivering fair products and innovative services in the insurance industry, focusing on underwriting, broking, and claims handling. Our subsidiaries, including GoSkippy and Vavista, serve over 700,000 customers. We are committed to values, culture, and customer service excellence, recognized by awards and growth. Join us to be part of a dynamic team that fosters creative thinking and personal development. We are proud to hold a Silver Accreditation from Investors in People.
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Machine Learning Operations Lead employer: Somerset Bridge
Contact Detail:
Somerset Bridge Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Operations Lead
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Azure, Databricks, and Postgres. Having hands-on experience or projects that showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the ML Ops field, especially those who have experience with cross-functional teams. Engaging in discussions on platforms like LinkedIn can help you gain insights and potentially get referrals for the position.
✨Tip Number 3
Prepare to discuss your problem-solving skills and collaborative experiences during the interview. Think of specific examples where you've successfully led a team or implemented a solution in a challenging environment.
✨Tip Number 4
Stay updated on the latest trends in ML Ops and cloud technologies. Being knowledgeable about recent advancements can demonstrate your passion for the field and your commitment to continuous learning.
We think you need these skills to ace Machine Learning Operations Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in ML Ops engineering, particularly with Azure and Databricks. Use specific examples that demonstrate your skills in API service development and collaboration with cross-functional teams.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for machine learning and your leadership experience. Mention how your background aligns with the responsibilities of overseeing the ML Ops platform and your familiarity with the technologies listed in the job description.
Showcase Problem-Solving Skills: In your application, provide examples of past challenges you've faced in ML Ops and how you successfully resolved them. This will demonstrate your excellent problem-solving skills and ability to work collaboratively.
Highlight Continuous Learning: Mention any recent courses, certifications, or projects related to ML Ops, Azure, or Databricks. This shows your commitment to staying updated in the field and your readiness to lead a team in a fast-paced environment.
How to prepare for a job interview at Somerset Bridge
✨Showcase Your Technical Expertise
Make sure to highlight your experience with ML Ops engineering, particularly with Azure and Databricks. Be prepared to discuss specific projects where you've successfully implemented these technologies, as this will demonstrate your capability to lead the development of the ML Ops platform.
✨Demonstrate Collaboration Skills
Since the role involves working closely with cross-functional teams, share examples of how you've effectively collaborated with data scientists, engineers, and other stakeholders in previous roles. This will show that you can thrive in a team-oriented environment.
✨Prepare for Problem-Solving Scenarios
Expect to face questions that assess your problem-solving skills. Think of challenges you've encountered in past projects, especially related to API services or microservices architecture, and be ready to explain how you overcame them.
✨Understand the SDLC Best Practices
Familiarise yourself with the Software Development Life Cycle (SDLC) best practices, as this is crucial for ensuring code is production-ready. Be prepared to discuss how you've applied these practices in your previous work, particularly in relation to peer reviews and pair programming.
