ML Ops Engineer at Thales

, , United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

20 Dec, 25

Salary

0.0

Posted On

21 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, DevOps, Python, Kubernetes, Docker, Linux, CI/CD, Automation, Machine Learning, Data Integration, Security Compliance, Agile Methodologies, Version Control, Problem Solving, Technical Documentation, Collaboration

Industry

Defense and Space Manufacturing

Description

Location: Crawley, United Kingdom In fast changing markets, customers worldwide rely on Thales. Thales is a business where brilliant people from all over the world come together to share ideas and inspire each other. In aerospace, transportation, defence, security and space, our architects design innovative solutions that make our tomorrow's possible. Together we offer fantastic opportunities for committed employees to learn and develop their career with us. At Thales UK, we research, develop, and supply technology and services that impact the lives of millions of people each day to make life better, and keep us safer. We innovate across the major industries of Aerospace, Defence, Security and Space. Your health and well-being matters to us and that’s why we offer you the flexibility to do what’s important to you; whether that’s part time hours, job sharing, home working, or the ability to flex your start and finish times. Where possible, we support a working pattern that suits your lifestyle and helps you reach your ambitions. ML Ops Engineer - CortAIx Crawley About CortAIx and Thales: At Thales, we focus on building and delivering robust, real-world AI and Data solutions that make a tangible impact for our customers—and society at large. Our global CortAIx initiative unites over 600 AI and data specialists dedicated to developing trusted, operationally effective AI-powered systems for some of the most challenging and complex environments. In the UK, CortAIx is accelerating this mission by fostering technology, talent, and research focused on ethical, transparent, and explainable AI. What sets this opportunity apart: We're looking for an MLOps Engineer who cares about building products and capabilities that really work in the field. At Thales, you’ll be empowered to create enduring solutions with broad impact, not just to develop prototypes or chase patents. Our structure supports long-term technical career growth, offering clear and supported paths for specialists and experts—so you can achieve mastery and broad influence without giving up hands-on technical work. Crawley may not have a large concentration of technical experts in every business line, but it brings you close to Thales UK’s IT core—giving you the chance to drive change at scale and influence the whole UK business. You'll enjoy both depth and breadth in your work, collaborating directly with business and technical teams. Your Impact and Environment: Join a practical, forward-thinking development team where you can influence ways of working—guiding and enabling data scientists to accelerate the translation of ideas into effective, operational features. You’ll play a key role as a force multiplier: not just delivering your own projects but elevating others and improving our collective output. Here, our mission isn’t to manipulate human attention for clicks or “likes”—we work with sensor data from a spectrum of sources, ranging from low-SWAP commodity sensors to the most advanced, exquisite solutions. You’ll engage deeply with colleagues from a wide range of highly technical sensor domains, developing your expertise and learning from specialists who are leaders in their field. Your work will be instrumental in empowering users to make sense of critical situations and support timely, high-consequence decisions. Primary Purpose of the Role: Drive the evolution, deployment, and scaling of AI and Data capabilities within Thales and for our customers, increasing both business growth and customer satisfaction through reliable and innovative solutions. Key Responsibilities and Tasks: Set up and configure ML environments and deployment tools such as Kubernetes, Docker, and Linux Containers. Write scripts to automate workflows and ensure the reproducibility of ML experiments and deployments. Conduct regular performance reviews and data audits of deployed models. Influence and collaborate with data scientists, championing best practices to efficiently translate concepts into robust product features. Troubleshoot issues related to model performance and technical infrastructure. Provide support and training to team members on MLOps tools and practices; champion knowledge sharing and reusable patterns. Create and maintain CI/CD pipelines for automating development, test, and deployment processes. Identify and drive the adoption of reusable solutions—enabling cost-effective delivery across multiple projects and teams. Collaborate with development and IT teams to deliver secure, scalable, and high-quality applications on the cloud, leveraging automation tools and scripts. Work with product owners to refine and meet user needs. Contribute actively to agile threat modelling and vulnerability management. Ensure the compliance of solutions with security and regulatory requirements—especially high assurance, MOD-related software. Support Customer/Solution Data Architects with data landscape coordination and cataloguing. Support and implement 3rd party data integrations for a wide range of use cases (internal and external). Skills and Experience Required: Experience in MLOps, DevOps, DevSecOps, or related software or AI engineering roles in complex, regulated environments. Proficiency with CI/CD deployment processes. Track record of deploying software/AI solutions in complex programmes, with an emphasis on operational reliability and scalability. Strong technical documentation and logical analytical skills—capable of problem-solving at both systems and detailed technical levels. Experience working on Linux-based infrastructure. Excellent knowledge of Python and at least one modern programming language for automation and ML development (e.g. Java). Experience with PyTorch and familiarity with other ML frameworks or libraries as needed (e.g., Scikit-learn, etc.). Understanding of supervised and unsupervised ML techniques and algorithms. Experience with model monitoring, logging, and performance evaluation tools (e.g., MLflow, Prometheus). Strong scripting skills in Bash, PowerShell, or similar for workflow automation. Experience with Linux Containers and orchestration platforms. Proficient in version control systems like Git. Ability to design secure, innovative solutions while adhering to strict security and assurance standards. Self-motivated to contribute, enable, influence, and inspire colleagues in technical fields. Security Clearance Statement: This role requires SC Clearance at minimum. If you don’t currently hold this level of clearance, you will need to undergo and successfully achieve SC Clearance. Please consult the UKSV NSV Agency for eligibility requirements and further guidance. What We Can Offer: We're committed to your technical development and success, providing market-leading training, mentoring, and continuous learning opportunities. You’ll have direct access to a community of technical specialists and experts—nurturing your growth, whether you aspire to deepen as a technical expert or broaden your impact across teams and disciplines. You’ll benefit from comprehensive packages: bonuses, private healthcare, structured career development, training budgets, and the support of a collaborative, diverse, and inclusive working environment. We make internal hiring a priority, so your progression opportunities at Thales—locally or globally—are significant. At Thales, we celebrate talent, encourage continuous learning, and value people as our most important asset. Join us to build real, meaningful solutions with impact beyond the ordinary #LI-CL1 In line with Thales' Baseline Security requirements, candidates will be asked to provide evidence of identity, eligibility to work in the UK and employment and/or education history for up to three years. Some vacancies may require full Security Clearance which can require further evidence to be provided. For further details of the evidence required to apply for Baseline and Security Clearance please refer to the Defence Business Services National Security Vetting (DBS NSV) Agency. At Thales we provide CAREERS and not only jobs. With Thales employing 80,000 employees in 68 countries our mobility policy enables thousands of employees each year to develop their careers at home and abroad, in their existing areas of expertise or by branching out into new fields. Together we believe that embracing flexibility is a smarter way of working. Thales UK is committed to providing an inclusive and barrier-free recruitment process. We will provide reasonable adjustments and support to ensure neuro-diverse applicants or those with a disability or long-term condition can be their best during the recruitment process. To request an adjustment, if you need this job advert in an alternative format or if you have any questions about the recruitment process, please contact Resourcing Ops for mid to senior roles, or the Early Careers Team for graduate and apprentice roles. Great journeys start here, apply now!

Responsibilities

Drive the evolution, deployment, and scaling of AI and Data capabilities within Thales and for customers. Influence and collaborate with data scientists to translate concepts into robust product features.