Senior Staff Machine Learning Engineer

As a Staff Machine Learning Engineer, you will drive AI programs, lead engagements, and independently develop innovative solutions that enhance decision-making, automate workflows, and create growth.

You will own the end-to-end development of AI-powered applications, from solution design to deployment, leveraging pre-trained machine learning and generative AI models. You will work closely with cross-functional teams, proactively identifying opportunities to integrate AI capabilities into Experian's products and services while optimizing performance and scalability.

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, create 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 realize their financial goals and help them 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. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

• Experinece working in cloud environment with one of Databricks, Azure or AWS
• 8+ years experience building data-drive products and solutions
• Experience leading AI engagements
• Strong experience with AI APIs (OpenAI, Hugging Face, Google Vertex AI, AWS Bedrock) and fine-tuning models for production use.
• Deep understanding of machine learning, natural language processing (NLP), and generative AI evaluation techniques.Key Responsibilities
  • Assist in Developing and Deploying Machine Learning Models: Support the development and deployment of machine learning models, including data preprocessing and performance evaluation in Python using sklearn, numpy and other standard libraries.
  • Build and Maintain ML Pipelines: Help build and maintain scalable ML pipelines, and assist in automating model training workflows in Python using MLFlow, Databricks, Sagemaker or equivalent.
  • Collaborate with Cross-Functional Teams: Work with product and data teams to align ML solutions with business needs and objectives.
  • Write Clean and Documented Code: Write clean, well-documented code, following best practices for testing and version control. Use Sphinx and other auto documentation solutions to automate document generation.
  • Support Model Monitoring and Debugging: Assist in monitoring and debugging models to improve their reliability and performance.
  • Participate in Technical Discussions and Knowledge Sharing: Engage in technical discussions, code reviews, and knowledge-sharing sessions to learn and grow within the team.
• Day-to-Day ActivitiesOn a daily basis, you will work closely with senior ML engineers and data scientists to support various stages of the machine learning lifecycle. Your day-to-day activities will include:
  • Data Preprocessing: Cleaning and preparing data for model training, ensuring data quality and consistency.
  • Model Training: Assisting in the training of machine learning models, experimenting with different algorithms and hyperparameters.
  • Performance Evaluation: Evaluating model performance using appropriate metrics and techniques, and identifying areas for improvement.
  • Pipeline Maintenance: Building and maintaining ML pipelines, ensuring they are scalable and efficient.
  • Code Development: Writing and maintaining clean, well-documented code, following best practices for testing and version control.
  • Model Monitoring: Monitoring deployed models to ensure they are performing as expected, and assisting in debugging any issues that arise.
  • Collaboration: Participating in team meetings, sprint planning, and daily stand-ups to stay aligned with project goals and timelines.

Our uniqueness is that we truly celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what truly matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's strong people first approach is award winning; Great Place To Work™ in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) 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 a critical 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, color, 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

Benefits

Experian care for employee's work life balance, health, safety and wellbeing. In support of this endeavor, we offer best-in-class family well-being benefits, enhanced medical benefits and paid time off.

Experian Careers - Creating a better tomorrow together

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