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For Companies At a Glance
- Tasks: Lead the design and development of innovative Generative AI solutions.
- Company: Join a forward-thinking consultancy at the forefront of technology.
- Benefits: Competitive daily rate, hybrid work model, and opportunities for professional growth.
- Why this job: Be a pioneer in Generative AI and make a significant impact on projects.
- Qualifications: Degree in a quantitative field and experience with data and AI models.
- Other info: Collaborative environment with a focus on cutting-edge technology.
The predicted salary is between 54000 - 60000 £ per year.
Job Description
Generative AI Lead6 monthsHybrid – 2-3 days per month on site in London£675 – 720 per day (Inside IR35)
Responsibilities-Leading on Generative AI solution design and developmentResearching and implementing cutting edge techniques, methodologies and approachesTaking projects from design, through proof of concept and into production and developing and delivering data science solutions using a variety of data sourcesLeading stakeholder management and issue resolution on project workIdentifying, sourcing, and engineering data to support data science activitiesCollaborating with other data professionals and business stakeholdersEnsuring all work is fully documented and quality assuredTaking solutions through internal governance and risk management processesExperience Required-Degree in a quantitative discipline (e.g., statistics, computing science, data science) or equivalent experienceExperience in dealing with high volumes of data with excellent attention to detailKnowledge of a wide variety of Generative AI modelsConceptual understanding of how large language models workProficiency in coding languages for data manipulation (e.g., SQL) and machine learning & AI development (e.g., Python)Experience with dashboarding tools such as Power BI and Tableau (beneficial but not essential)Experience with cloud native tooling for Azure and AWSStrong analytical and problem-solving skills
Disclaimer:
This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change.
Generative AI Lead employer: Advanced Resource Managers Limited
Contact Detail:
Advanced Resource Managers Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Generative AI Lead
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field and let them know you're on the hunt for a Generative AI Lead role. You never know who might have the inside scoop on opportunities or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects, especially those involving Generative AI. This will give potential employers a taste of what you can bring to the table and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of Generative AI models and coding languages like Python and SQL. Be ready to discuss your experience with data manipulation and how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! We’ve got some fantastic roles waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Generative AI Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Generative AI Lead role. Highlight your experience with AI models, data manipulation, and any relevant projects you've led. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific examples of projects you've worked on that relate to generative AI. Describe your role in the design and development process, and how you tackled challenges. This helps us understand your hands-on experience.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate a well-structured application that gets straight to the good stuff!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Advanced Resource Managers Limited
✨Know Your Generative AI Models
Make sure you brush up on the various Generative AI models before your interview. Be ready to discuss their strengths and weaknesses, and how they can be applied in real-world scenarios. This shows that you're not just familiar with the theory but also understand practical applications.
✨Showcase Your Coding Skills
Since proficiency in coding languages like SQL and Python is crucial for this role, prepare to demonstrate your skills. You might be asked to solve a problem on the spot or discuss your previous projects. Have examples ready that highlight your coding prowess and how you've used it in data manipulation or AI development.
✨Prepare for Stakeholder Management Questions
As a Generative AI Lead, you'll need to manage stakeholders effectively. Think of past experiences where you successfully navigated challenges or resolved issues with stakeholders. Be ready to share these stories, focusing on your communication and problem-solving skills.
✨Understand the Governance and Risk Management Processes
Familiarise yourself with internal governance and risk management processes relevant to data science projects. Be prepared to discuss how you ensure quality assurance and documentation in your work. This will demonstrate your attention to detail and commitment to delivering high-quality solutions.
