DescriptionIn CDAS at JPMorgan Chase our role involves solving challenging business problems through data science and machine learning techniques across all of Corporate technology and the supported Corporate Functions. corporate functions including Compliance Finance CAO Audit and Legal.
As an AI/ML Data Scientist/Engineer you will be responsible for designing developing and deploying cuttingedge AI and machine learning solutions to enhance the efficiency and effectiveness of our operations. You will work closely with crossfunctional teams to identify opportunities for automation and process improvement utilizing your expertise in machine learning and generative AI.
Job Responsibilities:
- Develop and implement machine learning models and algorithms to solve complex operational challenges.
- Design and deploy generative AI applications to automate and optimize business processes.
- Collaborate with stakeholders to understand business needs and translate them into technical solutions.
- Analyze large datasets to extract actionable insights and drive datadriven decisionmaking.
- Ensure the scalability and reliability of AI/ML solutions in a production environment.
- Stay uptodate with the latest advancements in AI/ML technologies and integrate them into our operations.
- Mentor and guide junior team members in AI/ML best practices and methodologies.
Key Skills and Qualifications:
- Ph.D. in Computer Science Data Science Machine Learning or a related field.
- Experience in deploying AI/ML applications in a production environment with skills in deploying models on AWS platforms such as SageMaker or Bedrock.
- Familiarity with MLOps practices encompassing 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 lightening or Scikitlearn.
- Proficiency in programming languages such as Python
- Proficiency in writing comprehensive test cases with a strong emphasis on using testing frameworks such as pytest to ensure code quality and reliability.
- Experience with generative AI models including GANs VAEs or transformers. Experience with Diffusion models is a plus.
- Solid understanding of data preprocessing feature engineering and model evaluation techniques.
- Familiarity with cloud platforms (AWS) and containerization technologies (Docker Kubernetes Amazon EKS).
- Excellent problemsolving skills and the ability to work independently and collaboratively.
- Strong communication skills to effectively convey complex technical concepts to nontechnical stakeholders.
Preferred Qualifications:
- Experience in the financial services industry particularly within investment banking operations.
- Experience in developing AI solutions using agentic frameworks.
- Experience finetuning SLMs with approaches like LoRA QLoRA and DoRA.
- Experience with prompt optimization frameworks such as AutoPrompt and DSPY to enhance the performance and effectiveness of prompt engineering.
- Familiarity with distributed computing systems frameworks and techniques like data sharding and DDP training
Required Experience:
Senior IC