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- Tasks: Design and develop generative AI models, support project delivery, and optimise AI code.
- Company: Join KPMG Curve, a cutting-edge tech venture focused on innovative AI solutions.
- Benefits: Enjoy fast-paced progression, learning allowances, paid overtime, and a strong work-life balance.
- Why this job: Be at the forefront of AI technology while making a real impact in a collaborative environment.
- Qualifications: BSc in Computer Science or related field; coding skills in generative AI and familiarity with AI/ML algorithms required.
- Other info: Hybrid role based in Leeds, with flexible hours and part-time options available.
The predicted salary is between 36000 - 60000 £ per year.
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Job description
Generative AI Engineer – KPMG Curve x5
Base Location: Leeds based (Hybrid – 2 days per week in office)
Experienced professional (
Note: Due to the nature of our work, applicants must hold or be capable of obtaining UK National Security Vetting, which may include residency requirements and UK nationality or dual nationality. Applications will not be considered if these are not met.
Join KPMG Curve, our latest tech venture, where we do things differently. We aim to solve big challenges and explore new opportunities, staying at the forefront of technology, especially in AI, coding, and innovative tech practices.
What’s in it for you?
- Fast-paced progression with continuous learning and innovation
- Opportunity to stay technical without moving into management roles
- Benefits like a learning allowance, paid overtime, and a focus on work-life balance
What will you be doing?
- AI Solution Development: Assist in designing and developing generative AI models for clients, work with senior engineers to implement solutions, and create PoCs and MVPs.
- Client Project Delivery: Support AI project delivery, collaborate across teams, and assist in client presentations.
- Coding & Implementation: Write and optimize AI code, deploy models using tools like TensorFlow, PyTorch, and cloud platforms.
- Data Management & Integration: Work with data teams to manage data pipelines, ensure data quality, and comply with data governance and privacy standards.
- Practise Building: Demonstrate AI potential to business teams, lead feasibility studies, and support client demos.
- Data Governance & Security: Ensure compliance with data policies and implement best practices in data privacy and ethical AI.
What will you need?
- BSc in Computer Science, Engineering, Statistics, or related field with a passion for AI
- Proficiency in coding generative AI models, prompt engineering, and LLMs
- Familiarity with AI/ML algorithms, cloud deployment, version control (Git), Docker, and containerization
- Strong communication skills and ability to work in cross-functional teams
Locations and Flexibility
This role is based in Leeds, with 2 days/week in the office. Flexible hours and part-time options may be available—discuss with our team.
Learn More & Apply
Explore our divisions and initiatives or get applying by creating a profile, uploading your CV, and making your mark at KPMG.
Join us to create next-level tech, make a difference, and swerve the mundane. Join KPMG Curve.
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Generative AI Engineer employer: KPMG-UnitedKingdom
Contact Detail:
KPMG-UnitedKingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Generative AI Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in generative AI and machine learning. Being well-versed in current technologies and methodologies will not only boost your confidence but also impress the interviewers at KPMG Curve.
✨Tip Number 2
Network with professionals in the AI field, especially those who work at KPMG or similar companies. Attend industry events, webinars, or meetups to make connections that could provide valuable insights and potentially refer you for the role.
✨Tip Number 3
Prepare to discuss your previous projects involving generative AI models. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will demonstrate your practical experience and problem-solving skills.
✨Tip Number 4
Showcase your coding skills by contributing to open-source projects or creating your own projects related to AI. This hands-on experience can set you apart from other candidates and provide concrete examples to discuss during interviews.
We think you need these skills to ace Generative AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI, coding, and any relevant projects. Emphasise your proficiency with tools like TensorFlow and PyTorch, as well as your understanding of data governance and privacy standards.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your ability to work in cross-functional teams. Mention specific experiences that align with the job description, such as developing generative AI models or collaborating on client projects.
Showcase Relevant Projects: If you have worked on any projects related to generative AI or machine learning, include them in your application. Describe your role, the technologies used, and the outcomes achieved to demonstrate your hands-on experience.
Highlight Communication Skills: Since strong communication skills are essential for this role, provide examples in your application where you've successfully collaborated with others or presented technical information to non-technical audiences.
How to prepare for a job interview at KPMG-UnitedKingdom
✨Showcase Your Technical Skills
Be prepared to discuss your experience with generative AI models and coding. Bring examples of your work, such as projects or code snippets, to demonstrate your proficiency in tools like TensorFlow and PyTorch.
✨Understand the Company Culture
KPMG Curve values innovation and collaboration. Research their recent projects and initiatives to show that you align with their mission and are excited about contributing to their tech ventures.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about how you would approach AI solution development and client project delivery, and be ready to articulate your thought process.
✨Emphasise Communication Skills
Strong communication is key in cross-functional teams. Be ready to discuss how you've effectively collaborated with others in past projects, and highlight your ability to present complex ideas clearly to clients.
