Senior Associate, AI ML Platform Engineering at JPMC Candidate Experience page

Jersey City, New Jersey, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Aug, 26

Salary

195000.0

Posted On

07 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

GenAI, MLOps, Python, Java, AWS, RAG, Kubernetes, Docker, Microservices, Prompt Engineering, LLM, API Development, CI/CD, Vector Search, ModelOps, Agentic AI

Industry

Financial Services

Description

Join the AI/ML Data Platforms team to build products that drives MLOps, automated governance and ML data development to accelerate a diverse and broad portfolio of AI/ML projects in one of the largest financial services firms in the world. We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As an Applied AI/ML Senior Associate at JPMorgan Chase within the Corporate AI/ML Data Platforms team, you will build a set of products that covers Agentic Ops, MLOps, ModelOps, ML data development (e.g. processing, data annotation) for firm wide ML practitioners. Job responsibilities * Works on several new systems including model repository/registry, feature registry, automatic model promotion policy engine, model & GenAI governance tools, data annotation, data preparation and lineage to help accelerate AI/ML in JPMC with the best user experience and sound governance. * Design, develop, and deploy GenAI and Agentic AI solutions that improve automation, decision-making, and user experience across business workflows. * Build LLM/SLM - powered applications including RAG-based systems, summarization/extraction pipelines, chat/coplay experiences, and tool-using agents. * Engineer production-grade services using Java and/or Python (GraphQL/REST/gRPC APIs, microservices, libraries), following secure coding and reliability best practices. * Develop new products leveraging cloud technologies and micro-services architecture patterns, identify new open-source libraries, using unfamiliar technologies and learning new programming languages to meet technical requirements. * Develop prompt strategies and prompt engineering assets (templates, routing, guardrails), and implement automated evaluation to improve quality over time. * Build and maintain data pipelines and processing workflows required for ML/GenAI use cases using cloud services. * Apply MLOps practices across the lifecycle: experimentation, versioning, CI/CD, deployment, monitoring, and maintenance for models/prompts/agents. * Implement robust testing (unit/integration), performance benchmarking (latency/cost), and observability (logging/metrics/tracing) for AI services. * Collaborate with cross-functional stakeholders to define requirements, success metrics, and rollout plans; communicate complex topics clearly to technical and non-technical audiences. Required qualifications, capabilities, and skills * Graduation or master’s degree (or equivalent practical experience) in Computer Science, Data Science, Machine Learning, or related field. * Hands-on experience building applied AI/ML or GenAI solutions (e.g., RAG, classification, extraction, ranking, summarization, copilots). * Familiarity with MCP (Model Context Protocol), Agent Skills and architectures that connect models to tools/data through standardized interfaces. * Familiarity with LLM application patterns: embeddings/vector search, prompt orchestration, tool calling/function calling, safety/guardrails, evaluation. * Strong software engineering experience delivering production systems; ability to design maintainable architectures and write clean, testable code. * Proficiency in Java and/or Python and experience building APIs/services and integrating with data sources and downstream systems. * Experience deploying solutions on AWS and cloud-native environments; understanding of security fundamentals and operational excellence. * Experience with modern engineering practices: CI/CD, code reviews, unit testing (e.g., pytest/JUnit), and deployment automation. * Experience with containers and orchestration (e.g., Docker, Kubernetes/EKS/ECS) and production monitoring practices. * Ability to communicate complex ideas effectively * Passion for growing your skills, tackling interesting work and challenging problems Preferred qualifications, capabilities, and skills * Experience building agentic AI systems (multi-step workflows, tool routing, planning, memory patterns, supervision/fallback strategies). * Experience with AWS Bedrock and/or SageMaker (or equivalent managed ML/GenAI platforms) and deployment patterns for scalable inference. * Experience with evaluation frameworks and approaches (golden datasets, LLM-as-judge, human-in-the-loop review, red teaming). * Experience fine-tuning models (e.g., LoRA/QLoRA/DoRA) and/or working with SLMs, embeddings, and retrieval systems. * Experience with developer productivity tooling such as GitHub Copilot and Claude Code, paired with strong SDLC controls. * Knowledge of the financial services industry and operating in regulated environments (auditability, controls, data handling). * Exposure to distributed compute/training concepts (e.g., DDP, sharding) and performance/cost optimization. #LI-RB1 JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 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. Visit our FAQs [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Responsibilities

Build and deploy GenAI and Agentic AI solutions, including RAG-based systems and MLOps platforms, to accelerate AI/ML projects. Develop production-grade microservices and data pipelines using Java and Python within a cloud-native environment.