At a Glance
- Tasks: Develop innovative GenAI solutions and collaborate with diverse teams to drive product delivery.
- Company: Join Experian, a global leader in data and technology, making a real impact.
- Benefits: Enjoy hybrid working, competitive pay, generous leave, and a focus on wellness.
- Other info: Experience a supportive culture that values diversity and personal growth.
- Why this job: Be at the forefront of AI innovation and shape the future of technology.
- Qualifications: Degree in STEM, programming skills, and a passion for machine learning.
The predicted salary is between 36000 - 60000 € per year.
Like the look of this opportunity Make sure to apply fast, as a high volume of applications is expected Scroll down to read the complete job description.
We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.
We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.
Job Description The Generative AI Centre of Expertise (GenAI CoE) at Experian exists to improve our products, our internal processes and our daily work through GenAI and process automation. The team is a mix of ML engineers, data scientists and product owners, who are dedicated to the next wave of innovation using GenAI.
Reporting into our Head of Machine Learning Product Engineering you will drive the delivery of concepts and ideas into products and services that Experian can take to their customers, whether that be businesses or direct to consumers. To do this, we build upon the outcomes of our experiments to meet the product requirements - considering performance, maintainability, and scalability. We, alongside the data scientists in the team, collaborate with a range of stakeholders.
You will:
Partner with teams across the organisation to develop GenAI solutionsfrom early experimentation to full-scale productionpotentially including DevOps work where needed.
Architect and build high-performant solutions, which may involve traditional ML modelling or large datasets, as well as GenAI.
Discover and introduce new technologies to the team, staying up to date with the latest approaches that enable the next generation of Experian\'s products with GenAI and ML.
Spend 10% of your work time on learning and sharing expertise on generative-AI technologies.
Qualifications Have a degree or equivalent qualification in a STEM subject.
Familiar with Unix environments.
Exposure to at least one other programming language besides Python.
Proficiency in object-oriented programming (OOP), SOLID principles, and test-driven development (TDD).
Proficiency with Docker and experience working with container orchestration tools such as Kubernetes, Docker Swarm, or cloud-based alternatives.
Comfort working across the full development stack, especially for prototyping.
Passion for applying GenAI and machine learning across diverse domains and throughout the full project lifecycle.
Experience with common ML approaches (e.g., LLMs, GBMs, deep learning) and typical software architectures.
Experience as a lead developer solving complex problems at scale.
Experience mentoring junior engineers.
Familiarity with various machine learning frameworks and toolkits (e.g., scikit-learn, XGBoost, TensorFlow).
Hands-on experience building GenAI solutions using patterns such as Retrieval-Augmented Generation (RAG) or fine-tuning Large Language Models (LLMs).
Greater familiarity with AWS compared to other cloud computing platforms.
Have experience developing REST APIs.
Additional Information Benefits package includes:
Hybrid working
Great compensation package and discretionary bonus
Core benefits include pension, bupa healthcare, sharesave scheme and more
25 days annual leave with 8 bank holidays and 3 volunteering days. You can purchase additional annual leave.
We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian\'s people first approach is award-winning; World\'s Best Workplaces 2024 (Fortune Top 25), Great Place To Work in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.
Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian\'s DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Experian Careers - Creating a better tomorrow together
Find out what its like to work for Experian by clicking here
Experian Careers - Creating a better tomorrow together
Find out what its like to work for Experian by clicking here
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Machine Learning Engineer - GenAI employer: Experian Ltd
Experian is an exceptional employer that prioritises employee growth and well-being, offering a hybrid working model and a comprehensive benefits package that includes generous annual leave, healthcare, and a focus on diversity, equity, and inclusion. With a strong commitment to innovation and collaboration, employees are encouraged to develop their skills in a supportive environment, making it an ideal place for Machine Learning Engineers looking to make a meaningful impact in the field of Generative AI.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - GenAI
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Experian. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or GitHub with projects related to GenAI or machine learning, make sure to highlight it. It’s a great way to demonstrate your expertise beyond just words.
✨Tip Number 3
Prepare for the interview by brushing up on common ML approaches and tools mentioned in the job description. We want to see your passion for GenAI and how you can apply it in real-world scenarios.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Machine Learning Engineer - GenAI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with GenAI, ML frameworks, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about GenAI and how you can contribute to our team. Be genuine and let your personality come through – we love seeing the real you!
Showcase Your Projects:If you've worked on any cool projects related to machine learning or GenAI, make sure to mention them! Include links to your GitHub or any other platforms where we can see your work. We’re all about innovation and creativity!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you're serious about joining our awesome team at Experian!
How to prepare for a job interview at Experian Ltd
✨Know Your GenAI Stuff
Make sure you brush up on the latest trends and technologies in Generative AI. Be ready to discuss how you've applied these concepts in your previous work or projects. Showing that you're not just familiar but passionate about GenAI will definitely impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in machine learning projects and how you tackled them. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help demonstrate your analytical thinking and ability to deliver high-performant solutions.
✨Get Comfortable with the Tech Stack
Familiarise yourself with the tools and technologies mentioned in the job description, like Docker, Kubernetes, and AWS. If you have hands-on experience, be ready to share examples of how you've used these tools in your projects. This shows you're not just a theorist but someone who can hit the ground running.
✨Be Ready to Collaborate
Experian values teamwork, so prepare to discuss how you've worked with cross-functional teams in the past. Highlight any mentoring experiences as well, as they show leadership potential. Being able to communicate effectively with both technical and non-technical stakeholders is key!
