Lead Software Engineer - AIML
Lead Software Engineer - AIML
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Job Description
We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.
As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking CAMP Technology youare an integral part of an agile team that works to enhance build and deliver trusted marketleading technology products in a secure stable and scalable way. You will play a key role as an experienced member of our global team. Your responsibilities will include business problems through data analysis building cutting edge ML and LLM models and deploying and supporting production grade models on AWS or Azure addressing.
Job responsibilities
- Responsible for setting direction development and implementation of ML and GenAI driven solutions
- Develop and implement machine learning models and algorithms to solve complex business and operational use cases.
- Design and deploy generative AI applications to automate and optimize business processes.
- Conduct research on prompt engineering techniques to improve the performance of promptbased models within the financial services field exploring and utilizing LLM orchestration and agentic AI libraries.
- Analyze large datasets to extract actionable insights and drive datadriven decisionmaking.
- Ensure the scalability and reliability of AI/ML solutions in a production environment.
- Collaborate with crossfunctional teams to identify requirements and develop solutions to meet business needs within the organization
- Communicate findings and insights to stakeholders through presentations reports and visualizations.
- 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.
Required qualifications capabilities and skills
- Formal training or certification onsoftware engineeringconcepts and 5 years applied experience
- Proven 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.
- Hands on experience in machine learning frameworks such as TensorFlow PyTorch Pytorch Lightning or Scikitlearn.
- Proficiency in programming languages such as Python Java etc.
- 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.
- 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.
- Experience in using GenAI (OpenAI or AWS Bedrock) to solve business problem.
- Experience with large scale training validation and testing
- Experience finetuning LLMs with approaches like LoRA QLoRA and DoRA.
- Solid understanding of AI/ML algorithms and techniques including deep learning reinforcement learning and natural language processing (NLP).
- Familiarity with AI/ML libraries and frameworks such as TensorFlow PyTorch scikitlearn and Keras as well as LLM frameworks such as LangChain LangGraph etc.
- Deep knowledge in Data structures Algorithms Machine Learning Data Mining Information Retrieval Statistics.
- Expert knowledge of one of the cloud computing platforms preferred: Amazon Web Services (AWS) Azure Kubernetes.
Employment Type
Full-Time
