Descripción del puesto

About the Role - Machine Learning Engineer The Global Analytics and AI team is accelerating Experian’s impact by bringing together data, tech, and data science and build game-changing products and services for our customers. We are looking for a Machine Learning (ML) Engineer to support the development of our AI platform and products to serve the needs of Experian’s clients, including those in the financial services. Our team is tackling key questions, like - How can we ensure successful adoption, integration, and utilization of our ML/AI solutions by our clients and internal teams? How can we increase the rigor and scalability of our products to unlock maximum value for our business? As a growing team, we embrace a start-up mentality while operating in a large organization. We value speed, agility, and impact – and our results and ways of working are transforming the culture of the larger organizations around us.

The profile need ADVANCED ENGLISH.

Responsibilities -

• Develop and maintain a scalable machine learning framework for data science products
• Work closely with our data scientists to pilot our products with beta customers
• Collaborate with cross-functional teams to understand business requirements and design Gen AI solutions that address complex challenges.
• Evaluate and select appropriate algorithms and methodologies to solve specific problems and optimize performance.
• Lead the refinement and iteration of prompt engineering techniques to enhance the effectiveness and efficiency of Gen AI systems.
• Experiment with retrieval-augmented generation (RAG) approaches to improve the relevance and coherence of AI-generated outputs.
• Work closely with software engineers and AI researchers to integrate prompt engineering and RAG components into production systems and ensure seamless deployment.

Qualifications - Bachelor’s degree in computer science, engineering, or related field.

Required Skills - Experience with common data science algorithms and processes (e.g., xgboost, hyperparameter tuning) Advanced knowledge in Python/PySpark and SQL Experience working with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) Experience with prompt engineering techniques and experience in refining and iterating on prompts for AI models Knowledge of retrieval-augmented generation (RAG) methodologies and experience in implementing RAG-based approaches for text generation tasks Interest or previous experience in financial services and/or credit modeling Excellent problem-solving skills, critical thinking abilities, and attention to detail Effective communication skills and the ability to collaborate effectively in a team environment.

Requisitos

Experience with common data science algorithms and processes (e.g., xgboost, hyperparameter tuning) Advanced knowledge in Python/PySpark and SQL Experience working with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) Experience with prompt engineering techniques and experience in refining and iterating on prompts for AI models Knowledge of retrieval-augmented generation (RAG) methodologies and experience in implementing RAG-based approaches for text generation tasks Interest or previous experience in financial services and/or credit modeling Excellent problem-solving skills, critical thinking abilities, and attention to detail Effective communication skills and the ability to collaborate effectively in a team environment.

Beneficios

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