Software Engineer II - Applied AI

As a Software Engineer II - Applied AI in the AI/ML for Engineering team at JPMorganChase, you'll be at the forefront of AI innovation, combining cutting‑edge techniques with unique data assets to optimise business decisions and automate processes. This role offers a unique blend of artificial intelligence and software engineering, allowing you to advance engineering processes and build impactful products. In this role, you will leverage the latest research in Large Language Models, Natural Language Processing and statistical machine learning to build AI‑powered products that automate processes and enhance decision‑making. You will collaborate with engineering and testing teams to design scalable Machine Learning services and communicate AI capabilities to diverse audiences.

Job Responsibilities

• Development of advanced machine learning models to address complex operational challenges.
• Evaluating and communicating the impact brought by proposed solutions.
• Architect and oversee the deployment of generative AI applications and agents to automate and enhance business processes.
• Collaborate with senior stakeholders to understand strategic business needs and translate them into comprehensive technical solutions.
• Analyze large datasets to extract actionable insights and support data‑driven decision‑making at a strategic level.
• Ensure the scalability, reliability, and security of AI/ML solutions in a production environment, with a focus on long‑term sustainability.
• Stay informed about the latest advancements in AI/ML technologies and drive their integration into our operations.
• Mentor and guide junior team members, fostering a culture of innovation and continuous learning.

Required Qualifications, Capabilities, And Skills

• Advanced degree in a STEM field (Degree in Computer Science or Software Engineering), with experience in AI/ML.
• Proven track record of AI/ML model development and deployment of AI/ML applications in a production environment, with expertise in deploying models on AWS platforms.
• Deep familiarity with MLOps practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
• Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit‑learn.
• Proficiency in Python with a strong emphasis on code quality and reliability through comprehensive testing.
• Extensive experience with generative AI models, mainly as cloud service APIs (e.g., OpenAI).
• Experience with integrating user feedback to establish self‑improving AI applications.
• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with cloud platforms (AWS).
• Excellent problem‑solving skills and the ability to work independently and collaboratively.
• Strong communication skills to effectively convey complex technical concepts to non‑technical stakeholders.

Preferred Qualifications, Capabilities, And Skills

• A Ph.D. is a plus but not required.
• Experience in software engineering practices.
• Experience in developing AI solutions using agentic frameworks.
• Experience fine‑tuning LLMs with advanced techniques.
• Experience with prompt optimisation to enhance the performance and effectiveness of prompt engineering.
• Demonstrated ability to design and implement AI application architecture.
• Significant experience in bringing AI applications to production with a focus on strategic impact and innovation.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.