At a Glance
- Tasks: Transform business challenges into innovative AI solutions and collaborate with a dynamic team.
- Company: Join Thales UK, a leader in high-impact AI capabilities.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Why this job: Make a real difference in AI while working on exciting projects.
- Qualifications: 5+ years in AI/ML with strong Python skills and collaborative experience.
- Other info: Diverse workplace committed to equal opportunities and career advancement.
The predicted salary is between 36000 - 60000 ÂŁ per year.
About the Company: Thales UK is committed to delivering high-impact AI capabilities across its businesses and to customers, enhancing the quality of offers, winning new business, and improving customer satisfaction.
About the Role: As part of a growing software and AI team in CortAIx Factory, the AI Engineer will collaborate with product owners, domain experts, data engineers, and software engineers to turn business problems into robust, secure, and scalable AI solutions.
Responsibilities:
- Translate business needs into AI solution designs, clear requirements, and measurable success criteria.
- Design, implement, and evaluate ML/AI models (e.g., classical ML, deep learning, computer vision, NLP/LLMs, timeâseries).
- Build robust training and evaluation pipelines, including data preprocessing, feature engineering, augmentation, and experiment tracking.
- Ensure Responsible AI practices: model robustness, safety, explainability (e.g., SHAP/LIME), bias assessment, and alignment with MOD/regulatory requirements.
- Package AI models as secure services/APIs and collaborate with software engineers to productionise, monitor, and continuously improve models.
- Define operational metrics and feedback loops for model performance, data quality, and drift; support postâdeployment reviews.
- Write secure, highâquality production code, unit/integration tests, and conduct peer code reviews.
- Produce clear technical documentation (designs, model cards, experiment reports) to a high standard.
- Create reusable AI components, templates, and reference implementations; contribute to the internal catalogue of capabilities.
- Support bids, PoCs, demos, and stakeholder workshops; communicate technical concepts to nonâtechnical audiences.
- Work with data engineers and architects on data acquisition, labelling strategies, integration of thirdâparty data, and data quality management.
- Participate in agile threat modelling and vulnerability management for AI features; adopt best practices for secure AI.
- Horizon scan for major AI technology trends; run trials and share best practices to accelerate responsible adoption.
Qualifications:
- 5+ years' experience delivering AI/ML solutions in complex, safetyâ or missionâcritical domains (e.g., defence, aviation, rail, medical, or similar).
- Proven track record of taking AI projects from discovery through model development to production handover, with measurable outcomes.
- Significant handsâon experience in at least one area: deep neural networks, computer vision, or timeâseries analytics.
- Highâquality technical documentation and stakeholder communication.
- Collaboration within crossâfunctional engineering teams.
Required Skills:
- Strong Python programming skills; proficiency with modern software engineering practices (testing, code quality, CI).
- Expertise in ML/DL algorithms and techniques for supervised, unsupervised, and, where relevant, reinforcement learning.
- Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikitâlearn, Hugging Face Transformers; OpenCV for vision.
- Experiment tracking and reproducibility tools (e.g., MLflow, Weights & Biases).
- Data wrangling and analysis (Pandas, NumPy, SQL); familiarity with Spark or similar is a plus.
- Model optimisation and deployment fundamentals: ONNX, TorchScript, FastAPI/gRPC; GPU acceleration (CUDA basics desirable).
- Responsible AI and security awareness: explainability, privacyâpreserving methods (e.g., differential privacy, federated learning), adversarial robustness.
- Proficient with Git and collaborative development workflows.
- Awareness of Agile and DevOps principles; ability to work effectively with MLOps for production deployment.
- Knowledge of cloud AI services (AWS/Azure/GCP) and containers (Docker) is desirable.
Preferred Skills:
- Governance of architecture or detailed designs throughout the project lifecycle.
- Experience with largeâscale data initiatives, data labelling strategies, and data quality management.
- Familiarity with MLOps practices and cloud platforms for AI deployment.
- Contributions to openâsource AI projects, publications, or patents.
Pay range and compensation package: Competitive salary based on experience and qualifications.
Equal Opportunity Statement: Thales UK is committed to diversity and inclusivity in the workplace, ensuring equal opportunities for all candidates.
Artificial Intelligence Engineer in Crawley employer: Thales
Contact Detail:
Thales Recruiting Team
StudySmarter Expert Advice đ€«
We think this is how you could land Artificial Intelligence Engineer in Crawley
âšNetwork Like a Pro
Get out there and connect with people in the AI field! Attend meetups, webinars, or industry conferences. We canât stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
âšShow Off Your Skills
Create a portfolio showcasing your AI projects, especially those that highlight your experience with ML models and coding. We recommend using platforms like GitHub to share your work; itâs a great way to demonstrate your expertise to potential employers.
âšAce the Interview
Prepare for technical interviews by brushing up on your Python skills and understanding key AI concepts. We suggest practicing common interview questions and even doing mock interviews with friends to boost your confidence.
âšApply Through Our Website
Donât forget to check out our job listings on the StudySmarter website! Applying directly through us not only shows your interest but also gives you a better chance of being noticed by hiring managers.
We think you need these skills to ace Artificial Intelligence Engineer in Crawley
Some tips for your application đ«Ą
Tailor Your Application: Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with AI/ML solutions and how it aligns with the responsibilities mentioned in the job description. We want to see how you can bring value to our team!
Showcase Your Technical Skills: Donât hold back on showcasing your Python programming skills and familiarity with AI frameworks like PyTorch or TensorFlow. Include specific projects or achievements that demonstrate your expertise in ML/DL algorithms and model deployment. This is your chance to shine!
Communicate Clearly: When writing your application, keep it clear and concise. Use straightforward language to explain your technical experience and how you've collaborated with cross-functional teams. Remember, we appreciate good communication skills, especially when explaining complex concepts!
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way to ensure your application gets into the right hands. Plus, it shows us youâre genuinely interested in joining our team at Thales UK!
How to prepare for a job interview at Thales
âšKnow Your AI Stuff
Make sure you brush up on your knowledge of AI and ML concepts, especially those mentioned in the job description. Be ready to discuss your experience with deep learning, computer vision, and NLP. Prepare examples of projects where you've successfully implemented these technologies.
âšShowcase Collaboration Skills
Since the role involves working with cross-functional teams, think of specific instances where you've collaborated effectively with product owners, data engineers, or software engineers. Highlight how you communicated technical concepts to non-technical audiences, as this will demonstrate your ability to bridge gaps between teams.
âšPrepare for Technical Questions
Expect to face technical questions that test your understanding of Python programming, ML algorithms, and AI frameworks like PyTorch or TensorFlow. Practice coding problems and be ready to explain your thought process clearly. This will show your problem-solving skills and technical expertise.
âšUnderstand Responsible AI Practices
Familiarise yourself with responsible AI practices, including model robustness, safety, and explainability. Be prepared to discuss how you've ensured these principles in your past work. This is crucial for the role, so showing your awareness and commitment to ethical AI will set you apart.