Lead Machine Learning Platform Engineer

Job description

Location: Guildford/hybrid

Salary: Dep on exp + car allowance + annual bonus + benefits

 

Who we are

Allianz is a global insurance company serving across 70 different countries, but from the very first day you join our team you’ll know that your contributions are valued. We offer world class learning and career development opportunities, while we celebrate an inclusive culture.

 

At Allianz Commercial, we are a dynamic and innovative team of data scientists, data engineers, analysts dedicated to leveraging machine learning (ML) to drive business growth and enhance customer experiences. We work collaboratively to develop advanced ML models and algorithms that power our data-driven solutions. To further strengthen our ML capabilities and streamline our ML operations (MLOps), we are seeking a skilled and motivated Platform Engineer to join our data science team.

 

Role Overview

 

As a Platform Engineer at Allianz Commercial, you will work closely with our team of data scientists and data engineers to provision infrastructure and operationalize ML models and ensure their scalability, reliability, and performance. Your expertise in DevOps/MLOps and experience with the Azure cloud environment will be essential in designing and implementing end-to-end ML solutions. You will collaborate with cross-functional teams to identify infrastructure requirements, provision Azure Cloud Services, develop ML pipelines, and deploy ML models into production. This role requires strong technical skills, a solid understanding of Azure Cloud services and deployment/configuration processes, and experience with DevOps/MLOps best practices.

 

 

Responsibilities

 

·  Collaborate with data scientists and data engineers to understand ML requirements, and design and develop ML pipelines for data pre-processing, model training, model evaluation and model monitoring.
·  Manage builds, and configurations in production and pre-production environments on Azure provisioning Azure services requested working with IT teams.
·  Build, optimize, and deploy ML models on the Azure cloud environment, leveraging Azure Machine Learning services and tools.
·  Develop automated ML workflows and implement CI/CD practices to ensure smooth model deployment and retraining.
·  Model serving/inferencing from data apps like Streamlit and /or Dash Plotly or Flask, Angular applications.
·  Experience in designing & implementing key DevOps/MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments.
·  Design, deploy and manage APIs for model serving and leverage external API’s.
·  Implement monitoring and logging systems to track model performance, detect anomalies, and ensure model reliability and availability.
·  Collaborate with IT teams to deploy ML models into production environments, ensuring scalability and security.
·  Develop and maintain ML infrastructure, including version control systems, model repositories, and experiment tracking platforms.
·  Implement ML model testing frameworks and ensure comprehensive model validation and evaluation.
·  Deploy and configure virtual machines, storage, and networking components in Azure.
·  Stay up to date with the latest Azure cloud services, MLOps techniques, tools, and frameworks, and proactively recommend improvements to enhance our ML operations.
·  Document and communicate ML engineering processes, best practices, and guidelines to ensure the reproducibility and maintainability of ML solutions.
·  Collaborate with cross-functional teams to define project goals, requirements, and success metrics.

About you

 

·  Bachelor’s or master’s degree in computer science, Data Science, or a related field. Equivalent experience will also be considered.
·  Proven experience as a Platform Engineer or similar role, with a focus on ML model development and deployment in production environments. Experiment tracking with MLflow.
·  Strong understanding and hand on experience of Azure cloud services like Azure ML, Cognitive services, Synapse, AzureOpenAI, AKS.
·  Organize the orchestration of pipelines for ETL and machine learning training to streamline model development using Cron jobs, Azure functions, Airflow.
·  Automate the ML pipeline using MLOps tools and practices and optimize it for scalability and performance.
·  Containerize applications and manage the Kubernetes deployments, Helm charts as well as the infrastructure needed to deploy models including foundational LLM’s internally; from GPUs to vector databases and inference components.
·  Solid understanding of DevOps best practices and tools to automate software development and deployment processes, and CI/CD concepts and experience in implementing Github Actions and runners.
·  Ability to diagnose and resolve model performance, scalability, and deployment issues.  Familiarity with monitoring tools to track model performance, resource utilization, and system health.
·  Proficiency in programming languages such as Python, and knowledge of PySpark and Spark pool clusters as well as ML libraries and frameworks.
·  Proficiency with observability tools, such as: Prometheus and Grafana.
·  Infrastructure-as-Code(IaC)Terraform and/or Bicep (for Azure resource provisioning).
·  Extensive experience of Apigee, API gateway management or FastAPI.
·  Knowledge of software engineering best practices, including code review, testing, and documentation.
·  Identify and assist in leveraging of new, potential areas of technology, industry best practises that can be adopted to solve business problems.
·  Strong problem-solving skills and ability to handle complex engineering challenges.
·  Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.

 

 

What we will offer you

 

Recognised and rewarded for a job well done, we have a range of flexible benefits for you to choose from- so you can pick a package that’s perfect for you. We also offer flexible working options, global career opportunities across the wider Allianz Group, and fantastic career development and training. That’s on top of enjoying all the benefits you’d expect from the world’s number one insurance brand, including:

 

·  Annual bonus scheme
·  Car allowance
·  30 days holiday plus bank holidays
·  Private medical insurance
·  Contributory pension scheme
·  Life cover
·  Group Income Protection
·  Flexible buy/sell holiday options
·  Flexible working arrangements
·  A discount up to 50% on a range of insurance products including car, home and pet
·  Retail discounts

 

Our ways of working

Do you need some flexibility with the hours you work? Let us know as part of your application and if it’s right for our customers, our business and for you, then we’ll do everything we can to make it happen.

 

Here at Allianz, we are signatories of the ABIs flexible working charter. We believe in supporting hybrid work patterns, which balance the needs of our customers, with your personal circumstances and our business requirements. Our aim with this is to help innovation, creativity, and you to thrive - Your work life balance is important to us.

 

Our Purpose and Values

We secure your future

Be Brave | With Heart | Everyone Counts | Inspiring Trust

Our purpose and values are more than just words on a website - they are the why and how of Allianz. They influence everything we do and guide us how to do it. Created by our people, for our people, they shape our culture, bring us together, and inspire us to be the best. Building an inclusive culture for us all to succeed.

 

Diversity & Inclusion

At Allianz, we value diversity and inclusion and back this up with our accreditations. Allianz is EDGE certified for gender inclusion, members of the Women in Finance Charter, members of the Stonewall Diversity Champion programme, signatories of Business in the Community’s Race at Work Charter, and an Armed Forces Covenant gold standard employer.

 

We have a range of employee networks focusing on gender inclusion, cultural diversity, LGBTQIA+, disability and long term health conditions (including neurodiversity), intergenerational and life stages, parents and carers, mental wellbeing, menopause support and armed forces and veterans, all supporting you to bring your best and authentic self to work.

 

Join us - Let’s Care for Tomorrow