Mid-Level Machine Learning Engineer - Data Engineer II â Chase
Mid-Level Machine Learning Engineer - Data Engineer II â Chase
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Job Description
At Chase UK were redefining digital banking by harnessing cutting-edge technology to deliver seamless intuitive experiences for our customers. Our engineering team operates with a start-up mindset empowered to shape the future of banking through scalable reliable and innovative solutions. If youre passionate about operationalizing advanced machine learningincluding large language models (LLMs) and generative AIthis is the place for you.
As a Mid-Level ML Engineer within the International Consumer Bank at JPMorgan Chase youll work alongside ML scientists Data Engineers and software engineers to build deploy and maintain sophisticated machine learning solutions in production. Youll play a hands-on role in implementing ML pipelines deploying models (including LLMs) and developing the supporting infrastructure that keeps our AI-driven products robust and scalable.
Job Responsibilities:
- Build automate and maintain ML pipelines for deploying advanced models including large language models (LLMs) at scale.
- Collaborate with data engineers scientists and product owners to operationalize workflows for reliable seamless model deployment and monitoring.
- Implement monitoring logging and alerting for AI services ensuring performance security and compliance in production environments.
- Write clean maintainable and efficient Python code for ML tooling orchestration and infrastructure.
- Develop and maintain infrastructure as code (IaC) using tools such as Terraform or CloudFormation.
- Work with containerization and orchestration technologies (e.g. Docker Kubernetes) to support scalable and repeatable deployments of AI services.
- Apply robust software engineering best practicesversion control CI/CD code reviews testing and automationto all aspects of the ML lifecycle.
- Troubleshoot and optimize ML workflows from initial development through deployment and production support.
- Engage in cross-functional squads participating in technical discussions design reviews and continuous improvement initiatives.
- Contribute to team growth by sharing knowledge and mentoring junior engineers as needed.
Required Qualifications Capabilities and Skills:
- Strong software engineering background with deep proficiency in Python (and optionally Go or Java).
- Demonstrated experience deploying and maintaining LLMs (e.g. GPTs Llama) in production environments.
- Familiarity with frameworks and tooling for LLMs and generative AI (e.g. Transformers LangChain Haystack OpenAI Vertex AI).
- Experience operationalizing ML solutions in cloud-native environments (AWS GCP Azure).
- Proficiency with containerization and orchestration (Docker Kubernetes or similar) for scalable model deployment.
- Practical experience with infrastructure-as-code (Terraform CloudFormation etc.).
- Understanding of concurrency distributed systems and scalable API development for ML-powered applications.
- Experience with version control (Git) and CI/CD pipelines.
- Strong problem-solving skills attention to detail and a collaborative growth-focused mindset.
- Experience working in agile product-driven engineering teams.
Preferred Qualifications:
- Exposure to Retrieval-Augmented Generation (RAG) pipelines vector databases (e.g. Pinecone Weaviate Milvus) and knowledge bases with familiarity in integrating them with LLMs.
- Experience with advanced model monitoring observability and governance of LLMs and generative AI systems.
- Experience with data engineering or analytics platforms.
- Understanding of AI safety security and compliance best practices in production.
- Enthusiasm for learning and adopting the latest MLOps and AI technologies.
#ICB #ICBEngineering
Required Experience:
Manager
Employment Type
Full-Time
