Job Title: Factory AI/ML Ops Engineer
Site Location: Bristol/Crawley/Glasgow (with Hybrid working)
Travel Percentage: 10 – 30 % nationally and > 5% International
SC – DV capable (desirable)
Primary Purpose of the Role:
To drive the evolution and deployment of Data and AI capabilities within the businesses and to our customers in order to increase growth in orders and increased customer satisfaction.
As part of a newly established software development team, the Factory AI/ML Ops Engineer will work with both the development team and the end user in Thales UK businesses. Supporting the Thales UK Digital and Data strategy the Software support engineer will support the delivery software offerings into an internal catalogue of reusable/re-deployable capabilities focused around data and AI capabilities, helping deliver continuous evolution and deployment of factory developed software.
The role will interact with other data solutions architects and engineers across the business working in Data and AI: delivering data solutions that make up new or enhanced market offers; mature AI technologies for deployment in Thales businesses, and act as a technical expert in solutions used transversally throughout the business.
The role will be part of the Thales UK Data and Digital Competence Centre team to ensure that the technology strategy, human capabilities and opportunity pipeline is enabling the business strategy and growth. The role will connect with stakeholders across engineering, Thales UK and Group Digital Competence Centres thinking.
Principal Relationships:
Thales UK Data and Digital Teams – Digital Competence Centre – ‘Hub and Spokes’
Thales UK and International Data and Digital Engineering Teams
Thales Research organisations focusing on AI technologies
Key Responsibilities and Tasks:
* Set up and configure ML environments and deployment tools (e.g., Kubernetes, Docker).
* Write scripts to automate workflows and ensure reproducibility of ML experiments.
* Conduct regular performance reviews and data audits of deployed models.
* Work closely with data scientists to facilitate the transition of models from development to production.
* Troubleshoot issues related to model performance and infrastructure.
* Provide support and training to team members regarding ML Ops tools and practices.
* Participate in cross-functional teams to drive best practices in ML model development and deployment.
* Create and maintain CI/CD Pipelines to enable efficient deployment of code by automating development and deployment processes.
* Identify solution opportunities that focus on Reuse, maximising the return on development costs by reducing other programme development costs.
* Collaborate with development teams to enable the delivery of high-quality, secure, and scalable applications on the cloud with automated tools and scripts.
* Recommend best practices and ensure the products developed within the organization are robust, secure and scalable.
* Work with the product owner to address user needs.
* Develop secure and high-quality production code, perform code reviews and able to debug issues.
* Participate in agile threat modelling and vulnerability management.
* Ensure compliance with security and regulatory requirements for MOD and high Design assurance software.
* Develop solutions for where data can bring value to our offers and our customer.
* Support the Customer Enterprise/Solution Data Architects in coordinating the data landscaping and cataloguing for Thales UK.
* Support the Customer Enterprise and Solution Data Architects in the creation and influence of UK MoD standards for Data Management and solutions that support data management and integration.
* Work to implement 3rd party data integrations to support internal and external use cases.
* Working collaboratively with the various squads and technical roles to identify common issues and opportunities to improve operational and strategic delivery.
* Horizon scan for major disruptive technology trends (trend spotting) that affect business. Provide practical advice and best practices to overcome these challenges and successfully deliver the expected business outcomes.
Skills
Technical:
* Logical Analysis of technical solutions and problem solving.
* Experience working on Linux or Windows based infrastructure.
* Excellent understanding of modern programming languages such as Ruby, Python, Perl, and Java developing ML models and automation scripts.
* Experience with popular ML frameworks and libraries, such as TensorFlow, PyTorch, Scikit-learn, and Keras.
* Understanding of algorithms and techniques for supervised and unsupervised learning.
* Experience with tools for model monitoring, logging, and performance evaluation, such as MLflow or Prometheus.
* Strong scripting skills in Bash, PowerShell, or similar scripting languages for automation of tasks and ability to write reusable and maintainable code to streamline ML operations.
* Proficient in using version control systems like Git for managing code and collaboration with team members.
* Excellent troubleshooting skills.
* Awareness of critical concepts in DevOps and Agile principles.
* Knowledge of business ecosystems, SaaS, infrastructure as a service (IaaS), platform as a service (PaaS), SOA, APIs, open data, microservices, event-driven IT, predictive analytics, machine learning and artificial intelligence.
* General IT Knowledge (applications, storage, networks, IT infrastructure, Infrastructure, service level agreements, Asset management etc).
* Familiarity with information management practices, system development life cycle management, IT services management, infrastructure and operations, and EA and ITIL frameworks.
* Ability to design innovative solutions whilst adhering to strong security constraints.
Interpersonal Skills:
* Ability to engage and influence a diverse set of stakeholders (Product Engineering Leaders, Customer, Design Authorities, Project Management, IS/IT).
* Able to influence a wide range of people to get things done – needs to be highly effective in a matrix based organisation – a good team player.
* Excellent communication skills and interpersonal skills – encourages an open environment where information and ideas are shared and innovative thinking is stimulated. Will be adept at effectively building stakeholder relationships and working collaboratively with customer, supplier and internal teams.
* Team player with a sharp intellect, challenging approach and a “can do attitude.”
Experience:
Essential:
* In excess of 5 years’ experience in the defence Industry or Aviation/Medical in any related software/DevOps/DevSecOps/MLOps/AI roles.
* CI/CD deployment.
* Software/AI development and deployment in complex programmes.
* Strong Data and Application understanding with underpinning Infrastructure solution development.
* Technical Documentation production to a high standard.
Desirable:
* Governance of architecture or detailed designs throughout the project lifecycle.
* Previously undertaken solution development and implementation of a large scale Data projects.
Qualifications:
Essential:
* Degree/Masters, an equivalent in a relevant Software/AI subject, or equivalent experience.
Desirable:
* Certification in relevant modern software languages.
* Vendor related technical competence qualifications (for example MCITP & VCP / CCSE & CCNP).
* SAFe or Agile competence (with supporting qualifications).
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