AI Infrastructure Engineer

We are seeking a highly skilled Senior Data Scientist with expertise in Machine Learning, Artificial Intelligence, Large Language Models (LLMs), foundation models, and fine-tuning techniques. This position is ideal for someone who is passionate about building enterprise-grade AI & ML applications and applying cutting-edge techniques to real-world financial and payments challenges., * Design, build, and optimize Generative AI, LLM, and multimodal foundation models for enterprise fintech applications.

• Fine-tune or adapt open-source and proprietary models
• Build high-performance models for NLP, document intelligence, anomaly detection, risk scoring, predictive analytics, and decisioning use cases.
• Lead experimentation to evaluate model accuracy, scalability, and fairness.
• Partner with engineering teams to deploy models on cloud-based ML pipelines (Azure, AWS) & data platforms (Databricks & Snowflake)
• Work with large-scale structured and unstructured datasets across the payments and financial ecosystem.
• Implement model monitoring, drift detection, and continuous retraining strategies.
• Evaluate and operationalize new AI technologies, foundation model architectures, responsible AI frameworks, and emerging research.
• Drive POCs and innovation initiatives that enhance Fiserv s AI capabilities and differentiate our products.

Do you have experience in Statistical modeling?, Do you have a Master’s degree?, Need minimum 14+ years of exp. Data Scientist, with RAG AI, LLM, with strong Databricks and Snowflake exp. Must have skills. Python, TensorFlow ,PyTorch, Spark, data analysis ,Datamodeling., * Master s or PhD in Computer Science, Data Science, Machine Learning, AI, or related field.

• 8+ years of hands-on experience building and deploying machine learning models in production.
• Proven expertise with LLMs, transformer architectures, transfer learning, and model fine-tuning.
• Strong proficiency in Python, PyTorch or TensorFlow, and ML libraries such as Transformers.
• Experience with cloud ML platforms, containerization (Docker/Kubernetes), and MLOps tools.
• Solid understanding of statistical modeling, optimization, and evaluation methodologies.
• Strong communication skills and ability to collaborate in cross-functional, fast-paced environments.

Preferred Qualifications

• Experience working in fintech, payments, banking, or fraud/risk environments.
• Background in vector databases, RAG pipelines, and knowledge graph integration.
• Experience with data privacy, model governance, and Responsible AI frameworks.
• Contributions to open-source AI/ML communities or research publications.