Senior Associate - Machine Learning Engineer

JPMorganChase; Jersey City (NJ); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorganChase in Jersey City is seeking a Senior Associate, Data Scientist / Machine Learning Engineer to shape, build, and deploy next-generation AI/ML systems across pricing, campaign targeting, personalization, and related business use cases. This hands-on, individual-contributor role blends deep AI/ML expertise with strong software engineering to deliver production-grade solutions.

You will design agentic AI workflows, orchestrate LLM-based agents, and collaborate with data scientists and

Qualifications

• 4+ years of hands-on experience building, deploying, and scaling ML/AI systems in production.
• Hands-on experience developing agentic AI with LLM-based workflows and tool use.
• Broad expertise in ML, deep learning, generative AI, and statistical modeling.
• Strong Python production engineering skills, testing, version control, CI/CD.
• Experience with model validation, governance, monitoring, and MLOps tooling.
• Strong communication and ability to translate business problems to production solutions.

Responsibilities

• Design, develop, and deploy AI/ML systems from experimentation to production and monitoring.
• Build agentic AI workflows with multi-step reasoning and tool orchestration.
• Develop scalable ML infrastructure and pipelines with solid software engineering practices.
• Apply ML methods to pricing, marketing, campaign targeting, and customer analytics.
• Contribute to standards, reproducibility, and responsible AI practices.
• Collaborate with data scientists and engineers, participate in code reviews, mentor juniors.
• Communicate trade-offs and results to technical and non-technical stakeholders.
• Support model validation, governance, and risk management in production.

Skills

Python

ML Engineering

Agentic AI

LLMs

Model Deployment

CI/CD

Data Analysis

Education

Statistics

Computer Science

Applied Mathematics

Economics

Tools

PyTorch

TensorFlow

MLflow

Airflow

Job description

Job Description

As a Senior Associate, Data Scientist / Machine Learning Engineer within our ASSET & WEALTH MANAGEMENT (AWM) AI/ML team, you will contribute to the design, development, and production of next-generation AI/ML systems across pricing, campaign targeting, personalization, and related business use cases. This is a hands-on technical individual-contributor role for an exceptional engineer who blends broad, deep AI/ML expertise with a strong emphasis on agentic AI development together with strong machine learning engineering and software engineering skills. Beyond building models and agents, you will help build robust, scalable systems, contribute to technical direction under the guidance of senior team members, collaborate closely with engineers and stakeholders, and help translate complex business problems into production-grade solutions that drive measurable impact.

Job Responsibilities

• Contribute to the end-to-end design, development, and deployment of AI/ML and agentic AI systems from problem framing and experimentation through production, monitoring, and continuous improvement.
• Design and build agentic AI workflows and applications, including multi-step reasoning, tool use, orchestration, and LLM-based agents that automate and augment complex analytical and business processes.
• Help build and maintain scalable, reliable ML and agentic infrastructure and pipelines, applying strong software engineering practices (version control, testing, CI/CD, code review, modular design).
• Apply broad AI/ML methods including deep learning, generative AI/LLMs, and modern ML techniques to high-impact business problems in pricing, marketing, campaign targeting, and customer analytics.
• Contribute to technical standards and best practices, championing engineering excellence, reproducibility, and responsible AI/ML practices.
• Collaborate with data scientists and engineers, participating in code reviews and knowledge sharing, and supporting the mentoring of junior or intern staff as appropriate.
• Partner with product, business, and engineering teams to scope opportunities and communicate technical trade-offs and results to both technical and non-technical audiences.
• Support and apply model validation, governance, monitoring, and risk-management frameworks for models and agents in production.

Required Qualifications, Skills And Capabilities

• Solid experience (typically 4+ years) building, deploying, and scaling machine learning and AI systems in production environments.
• Strong, hands-on experience developing agentic AI systems including LLM-based agents, tool/function calling, multi-step reasoning, orchestration frameworks, and AI-assisted analytical workflows.
• Broad and deep expertise across modern AI/ML methods, including machine learning, deep learning, generative AI/LLMs, and statistical modeling.
• Deep, hands-on software engineering expertise: strong proficiency in Python (and/or other production languages), software design principles, testing, version control, CI/CD, and building production-grade code.
• Strong machine learning engineering skills, including experience with ML frameworks, model pipelines, feature stores, orchestration, and MLOps tooling.
• Strong quantitative training in Statistics, Data Science, Computer Science, Economics, Applied Mathematics, Operations Research, or a related field.
• Proven experience with model validation, diagnostic testing, and careful interpretation of model performance.
• Demonstrated ability to own and deliver technical projects and collaborate effectively within a team.
• Excellent ability to communicate complex technical findings clearly to both technical and non-technical audiences.
• Strong problem-solving skills and the ability to work independently in ambiguous, real-world settings.

Preferred Qualifications

• Experience building and deploying advanced agentic AI platforms, multi-agent systems, or retrieval-augmented generation (RAG) applications at scale.
• Industry experience applying AI/ML to pricing, marketing, campaign targeting, personalization, or customer analytics.
• Understanding of causal inference fundamentals (e.g., confounding, selection bias, treatment effect estimation) and modern causal ML methods such as meta-learners, uplift models, causal forests, or double machine learning is a good-to-have.
• PhD or a Master's in Statistics, Computer Science, Economics, Econometrics, or a related quantitative field is a plus.

ABOUT US

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 for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About The Team

J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.