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- Tasks: Design and implement advanced AI solutions to drive client success.
- Company: Leading digital services firm with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Shape impactful consulting solutions and work with cutting-edge AI technologies.
- Qualifications: Strong expertise in Python, generative AI, and scalable AI/ML solutions.
- Other info: Collaborative environment with a focus on Big Data and MLOps.
The predicted salary is between 48000 - 72000 £ per year.
A leading digital services firm is seeking a Senior Lead Analyst Data Science to design and implement advanced AI solutions. The role demands strong expertise in Python programming and generative AI, along with a proven track record of developing scalable AI/ML solutions using cloud technologies. Candidates with robust knowledge in Big Data, MLOps, and stakeholder collaboration are highly preferred. Join to shape impactful consulting solutions that drive client success across industries.
Senior AI/ML & Gen AI Architect employer: Infosys
Contact Detail:
Infosys Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI/ML & Gen AI Architect
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI/ML space on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that dream role.
✨Tip Number 2
Showcase your skills! Create a portfolio of your AI/ML projects, especially those involving Python and generative AI. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We recommend practising common interview questions related to AI/ML and thinking about how you can demonstrate your stakeholder collaboration experience.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior AI/ML & Gen AI Architect
Some tips for your application 🫡
Showcase Your Expertise: Make sure to highlight your strong expertise in Python programming and generative AI. We want to see how your skills align with the role, so don’t hold back on sharing your past experiences and projects!
Demonstrate Your Impact: When detailing your previous work, focus on the impact you made through your AI/ML solutions. We love seeing how you've driven client success and shaped consulting solutions in your past roles.
Highlight Collaboration Skills: Since stakeholder collaboration is key for us, be sure to mention any experiences where you worked closely with others. Show us how you’ve effectively communicated and collaborated to achieve great results.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our team!
How to prepare for a job interview at Infosys
✨Master the Tech Stack
Make sure you brush up on your Python programming skills and be ready to discuss your experience with generative AI. Prepare examples of scalable AI/ML solutions you've developed, especially those using cloud technologies, as this will show your technical prowess.
✨Showcase Your Big Data Knowledge
Familiarise yourself with Big Data concepts and tools. Be prepared to explain how you've leveraged Big Data in past projects and how it can enhance AI solutions. This will demonstrate your ability to handle large datasets effectively.
✨Highlight MLOps Experience
MLOps is crucial for this role, so come equipped with insights on best practices and tools you've used. Discuss any challenges you've faced in deploying machine learning models and how you overcame them to ensure smooth operations.
✨Emphasise Collaboration Skills
Since stakeholder collaboration is key, think of specific instances where you've worked with cross-functional teams. Share how you communicated complex AI concepts to non-technical stakeholders, showcasing your ability to bridge the gap between tech and business.
