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Lead MLOps Engineer – Telematics
Hastings Direct. Provide technical leadership on ML platform architecture .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning platform architecture, MLOps practices, and cloud-native technologies, with a strong focus on automation, scalability, and operational excellence. Collaborates effectively with cross-functional teams to deliver high-quality predictive models and data products.
Highest-signal resume keywords
Python ProgrammingMLOps ToolingCloud EnvironmentsSQL ProficiencyMachine Learning Solutions
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning ArchitectureAutomated WorkflowsFeature EngineeringModel TrainingModel DeploymentCI/CD PracticesInfrastructure AutomationObservability Best PracticesVersion ControlTesting Methodologies
Soft Skills
CollaborationCuriosityPragmatismIndependent WorkContinuous Improvement
Tools & Technologies
AzureAWSGCPContainerizationOrchestration
Industry Keywords
Data PlatformsPredictive ModelsTelematics DataGovernanceReproducibility
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Provide technical leadership on ML platform architecture
- Shape tooling, standards, and the operating model for machine learning delivery across the organisation
- Develop and maintain automated workflows for feature engineering, model training, testing, deployment, monitoring, and retraining
- Partner with Data Scientists, Data Engineers, and ML Engineers to operationalise predictive models and data products
- Establish best practices for ML observability, model performance monitoring, CI/CD, versioning, governance, and reproducibility
- Improve the reliability, scalability, and efficiency of machine learning and data platforms
- Work with cloud-native technologies and infrastructure-as-code for modern ML workloads
- Present technical solutions and outcomes to engineering, operational, and commercial stakeholders
- Evaluate emerging technologies and contribute to engineering standards and best practices
- Turn telematics data into underwriting advantage and support market-beating customer prices
Requirements
What you’ll need- Strong Python skills
- Experience building and operating machine learning solutions in cloud environments
- Experience with MLOps tooling and practices, including CI/CD, containerisation, orchestration, model deployment, monitoring, and infrastructure automation
- Experience using SQL and working with large-scale data platforms
- Familiarity with modern cloud platforms such as Azure, AWS, or GCP
- Experience collaborating with Data Scientists, Data Engineers, Software Engineers, Operational and Commercial stakeholders
- Understanding of software engineering best practices including testing, version control, code review, and observability
- Technical excellence and understanding of business outcomes
- Ability to work independently and collaborate across multidisciplinary teams
- Curiosity, pragmatism, and willingness to challenge existing approaches
- Passion for engineering quality, automation, and continuous improvement
- Successful completion of referencing process, including credit and criminal record checks
Benefits
Comp & perks- Car allowance
- Annual pay reviews
- Flexible and hybrid working approach
- Annual 4Cs performance bonus
- Private medical insurance
- 4x salary life assurance cover
- Income protection at no extra cost
- Pension contribution match up to 10%
- Discounts and cashback at everyday retailers and on Hastings products
- Fee-free independent mortgage advice
- Free access to financial wellbeing support
- Thrive mental health app
- Colleague assistance programme available 24/7
- In-house mental health first aiders
- Support groups and dedicated mental wellbeing support
- 27 days annual leave plus bank holidays
- Option to buy or sell one contracted week
- Healthcare cashback plans
- Dental plans
- Discounted health assessments
- Cycle to work scheme
- Tech schemes
- Discounted and free onsite facilities
- Social events throughout the year
- Training and development
- Recognition and rewards
- Support for reasonable adjustments during recruitment