Applied AI​/ML Senior Associate - Predictive Science

As an Applied AI/ML Senior Associate within the Commercial & Investment Bank technology team, you will build and fine-tune language models (including LLMs) that detect and categorize complaints and sentiment across client interactions (calls, chats, emails, surveys). You'll develop complaint taxonomies and multi-label classifiers, build training/validation/monitoring pipelines, deploy models with MLOps/data engineering partners, and ensure solutions meet privacy, regulatory, and model-risk standards.

• Build and fine-tune ML/NLP models (including LLMs) to detect and categorize complaints and sentiment within client interactions (calls, chats, emails, surveys) and develop taxonomies and multi-label classification systems for complaint types, severity, and root cause
• Evaluate, fine-tune, and deploy pre-trained language models; conduct prompt engineering and model evaluation as needed along with build data pipelines for training, validation, and continuous model monitoring
• Analyze model outputs to identify drift, bias, or degradation, and implement retraining strategies
• Ensure models meet regulatory, privacy, and model-risk governance standards
• Collaborate with data engineers and MLOps teams to product ionize models at scale
• Present findings and model performance metrics to technical and non-technical stakeholders

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field and 3+ years of experience building and deploying ML/NLP models in production
• Strong Python skills and experience with ML frameworks (PyTorch, Tensor Flow, Hugging Face Transformers) with hands-on experience fine-tuning or working with large language models
• Experience with text classification, NER, sentiment analysis, or topic modeling
• Familiarity with cloud ML platforms (AWS Sage Maker, Azure ML, or similar)
• Solid understanding of the ML lifecycle: data prep, training, evaluation, deployment, monitoring
• Strong communication skills and ability to work cross-functionally

• Familiarity with model risk management and regulatory requirements
• Experience with vector databases, retrieval-augmented generation (RAG), or LLM fine-tuning techniques (LoRA, PEFT)
• Knowledge of MLOps tools (MLflow, Kubeflow, Airflow)
• Exposure to text classification, NER, sentiment analysis, and cloud ML platforms preferred.

JPMorgan

Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility.

These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

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