Software Engineer III - AI/ML

JPMorgan Chase & Co.•Plano, TX

14h

About The Position

Join our dynamic AI team to design, develop, and deploy cutting-edge machine learning and AI solutions. You will work on scalable backend systems, real-time prediction models, and advanced automation flows, driving measurable business impact across multiple domains. You will also ensure that AI models and workflows adhere to cybersecurity best practices.

Requirements

Formal training or certification and 3+ years of experience with AI models and workflows
Advanced proficiency in Python and relevant libraries (Pandas, NumPy).
Hands-on experience with frameworks and libraries including TensorFlow, PyTorch, BERT/LLMs, Hugging Face, OpenCV, scikit-learn, SKLearn, Pandas, Flask and React.
Expertise in cloud and DevOps technologies, including AWS, Google Cloud, Azure, Docker, Kubernetes, Jenkins, and GitLab.
Skilled in working with databases such as MySQL, MongoDB, PostgreSQL, and NoSQL systems.
Strong background in data science and AI, covering deep learning, NLP, GenAI, RAG concepts, prompt engineering, and data visualization.
Experience in secure coding, model validation, and data privacy.
Excellent problem-solving, communication, and teamwork skills.

Nice To Haves

Experience with LLM fine-tuning, prompt engineering, and multi-modal AI integration.
Familiarity with CI/CD pipelines and automation tools.
Knowledge of frontend frameworks (React, Next.js).
Certifications in AI/ML, Kubernetes, AWS, or cybersecurity.
Exposure to cybersecurity frameworks and compliance standards.

Responsibilities

Lead the end-to-end design, development, and deployment of machine learning models and platforms, including LLMs, GANs, and recommendation engines.
Design, develop, and fine-tune AI/ML models for real-time user behavior prediction, churn reduction, and customer experience automation.
Apply RAG concepts, prompt engineering, anomaly detection, and changepoint detection to solve complex business problems.
Develop and maintain scalable cloud-native applications on AWS, Azure, or Google Cloud.
Build robust and scalable APIs for integrating machine learning models and backend systems.
Collaborate with cross-functional teams for model experimentation and solution integration.
Implement cybersecurity controls to safeguard AI workflows and ensure compliance.