ML Ops Engineer in Bristol

ML Ops Engineer in Bristol

Bristol Full-Time 36000 - 60000 £ / year (est.) No working from home possible
Thales

At a Glance

  • Tasks: Join our team as an ML Ops Engineer, driving AI solutions and enhancing customer satisfaction.
  • Company: Thales is a global leader in aerospace, defence, security, and space, innovating for a safer tomorrow.
  • Benefits: Enjoy flexible working hours, remote options, private healthcare, and opportunities for personal development.
  • Other info: This role requires SC Clearance; support for neuro-diverse applicants is available.
  • Why this job: Be part of cutting-edge AI innovation, collaborating with top talent in a supportive environment.
  • Qualifications: Experience in software/DevOps/MLOps roles, strong programming skills, and familiarity with ML frameworks required.

The predicted salary is between 36000 - 60000 £ per year.

ML Ops Engineer

Location: Bristol – Hybrid

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.

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.

#J-18808-Ljbffr

ML Ops Engineer in Bristol employer: Thales

Thales is an exceptional employer that prioritises the growth and well-being of its employees, offering a flexible work environment tailored to individual lifestyles. With a strong commitment to innovation in AI and technology, employees benefit from extensive training opportunities, mentorship from industry leaders, and a diverse, inclusive culture that fosters collaboration and creativity. Located in Bristol, a hub for technological advancement, Thales provides a unique chance to contribute to impactful projects that enhance safety and security globally.

Thales

Contact Details:

Thales Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land ML Ops Engineer in Bristol

Tip Number 1

Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Kubernetes, Docker, and popular ML frameworks like TensorFlow and PyTorch. Having hands-on experience or projects showcasing these skills can set you apart.

Tip Number 2

Engage with the Thales community on platforms like LinkedIn. Follow their updates, join discussions, and connect with current employees to gain insights into the company culture and expectations for the ML Ops Engineer role.

Tip Number 3

Prepare to discuss your experience with CI/CD pipelines and automation scripts during the interview. Be ready to share specific examples of how you've implemented these in past projects, as this is a key responsibility of the role.

Tip Number 4

Research Thales' recent projects and initiatives in AI and data solutions. Being knowledgeable about their work will not only help you tailor your responses but also demonstrate your genuine interest in contributing to their mission.

We think you need these skills to ace ML Ops Engineer in Bristol

Experience in ML Ops, DevOps, or related roles
Proficiency in CI/CD deployment processes
Strong understanding of modern programming languages (Python, Ruby, Java, Perl)
Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Keras)
Ability to set up and configure ML environments (Kubernetes, Docker)
Experience with model monitoring and performance evaluation tools (MLflow, Prometheus)
Strong scripting skills (Bash, PowerShell)

Some tips for your application 🫡

Tailor Your CV:Make sure your CV highlights relevant experience in ML Ops, DevOps, or AI roles. Focus on specific projects where you've set up ML environments, automated workflows, or collaborated with data scientists.

Craft a Compelling Cover Letter:In your cover letter, express your enthusiasm for the role at Thales and how your skills align with their needs. Mention your experience with tools like Kubernetes, Docker, and popular ML frameworks, and how you can contribute to their CortAIx initiative.

Showcase Technical Skills:Clearly list your technical skills relevant to the job description, such as programming languages (Python, Ruby), CI/CD practices, and experience with model monitoring tools. Use bullet points for clarity.

Highlight Problem-Solving Abilities:Provide examples of how you've tackled challenges in previous roles, particularly in deploying ML models or improving processes. This will demonstrate your analytical skills and ability to work under pressure.

How to prepare for a job interview at Thales

Understand the Role

Before your interview, make sure you thoroughly understand the responsibilities of an ML Ops Engineer at Thales. Familiarise yourself with their specific tools and technologies, such as Kubernetes, Docker, and popular ML frameworks like TensorFlow and PyTorch.

Showcase Your Experience

Be prepared to discuss your previous experience in software development, DevOps, or MLOps roles. Highlight any projects where you've set up ML environments, automated workflows, or collaborated with data scientists to transition models from development to production.

Demonstrate Problem-Solving Skills

Thales values logical analysis and problem-solving abilities. Be ready to provide examples of how you've tackled technical challenges in past roles, particularly those related to model performance and infrastructure troubleshooting.

Ask Insightful Questions

Prepare thoughtful questions about Thales' approach to AI and data solutions. Inquire about their current projects, team dynamics, and how they ensure compliance with security and regulatory requirements. This shows your genuine interest in the company and the role.