As a Software Engineer III, you will design and deploy LLM models and AI/ML pipelines, collaborate with cross-functional teams, optimize cloud infrastructure, conduct data preprocessing, and monitor deployed models. You will also communicate technical findings to stakeholders while staying updated on advancements in machine learning and NLP.
Job Description
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorgan Chase within the Asset & Wealth Management, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
- Design, develop, and deploy LLM models and pipelines to tackle business challenges and opportunities
- Utilize techniques like prompt engineering, model fine-tuning, RAGs, and LLM Agents for use cases such as Q&A, summarization, and automation
- Employ firm-standard tools and platforms to set up automated AI/ML pipelines that can be quickly re-trained and deployed
- Collaborate with stakeholders and cross-functional teams to gather requirements and comprehend ML/LLM use cases and data needs
- Optimize and maintain cloud-based infrastructure to facilitate rapid ML model deployment and integration with workflows
- Conduct data analysis and preprocessing to prepare datasets for model training and evaluation
- Monitor and maintain deployed models, implementing necessary updates and improvements to address business priorities and model drift
- Stay informed about the latest advancements in machine learning, GenAI, and NLP technologies
- Communicate findings and insights effectively to both technical and non-technical stakeholders.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Experience in ML/LLM model development, deployment, and integration.
- Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Good understanding of statistical concepts of hypothesis testing, data distributions and inference underlying and governing choice and working of ML algorithms.
- Strong fundamentals in natural language processing (NLP) and experience using large language models (LLMs) such as GPT, Llama, BERT, or similar.
- Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.
- Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and services like Sagemaker/Azure ML for deploying machine learning models.
- Strong problem-solving skills and the ability to work independently and collaboratively in a fast-moving organizational setup.
- Excellent problem-solving skills and the ability to work independently and collaboratively.
- Strong communication and interpersonal skills, with experience in working with stakeholders and cross-functional teams.
Preferred qualifications, capabilities, and skills
- Experience with big data technologies such as Spark is a big plus.
- Experience of CI/CD pipelines and DevOps practices/MLOps for ML model deployment.
- Demonstrable portfolio of projects and Open source community contributions.
Top Skills
Python
JPMorganChase Mumbai, Maharashtra, IND Office
B11, B9, B10, Nirlon Knowledge Park, near Mrinal Tai Gore Flyover, Cama Industrial Estate, Mumbai, Maharashtra, India, 400063
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