Generative AI Specialist - job 1 of 2

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, provide digital marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realise their financial goals and help them to save time and money.

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.

We are hiring an experienced and motivated Generative AI Specialist to join our team. You will develop and implement modern generative AI models and guide innovation across our organization. You will work with Data Scientists, Software Engineers, and Product Managers to develop AI-powered solutions that enhance our products and services.

What you'll do:

• Implement Generative AI models and algorithms using techniques such as GPT, VAE, and GANs.
• Build applications using LLMs and Gen AI.
• Build PoC (Proof of Concept).
• Improve existing Generative AI models for better performance.
• Maintain AI pipelines including data preprocessing, feature extraction and model training.
• Develop clear documentation including technical specifications.
• Contribute to the establishment of best practices for generative AI development.
• Manage reports on GenAI use case performance and outcomes.
• Monitor project progress and provide regular updates to stakeholders.
• Help develop Gen AI project plans.
• Support the analysis for GenAI project requests. Define project scope, goals, and deliverables while ensuring understanding of our goals.

What you'll bring:

• Around 3 years of experience in Artificial Intelligence.
• Higher Education Degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
• Familiar with AWS, Azure, GPT, Llama or other LLM.
• Knowledge of Natural Language Processing (NLP).
• Experience with Database(PostgreSQL, MongoDB or similar).
• Excellent written and verbal English skills.
• Knowledge of or experience with Python and Machine Learning libraries and frameworks.
• Knowledge of data structures, algorithms, and software engineering principles.
• Familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.
• Knowledge of Agile or Scrum.
• Collaborative, Proactive and Communicative Team Player.
• DevOps- CI/CD knowledge & work experience (will be an advantage).
• Experience in Gen AI or Tech transformation Program/Projects (will be an advantage).

You will get:

• Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books.
• Work environment - excellent work conditions with friendly environment, recognized strong team spirit, and fun and quality recreation time.
• Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
• Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
• Opportunity for Flexible working hours and Home Office.

Experian is an Equal opportunity employer. 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.

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