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Chase · 4 months ago

Applied AI ML, Sr Associate

575 Washington Blvd, Jersey City, NJ, 07310, US

Full-time

Onsite

Mid, Senior Level

$128K/yr - $195K/yr

4+ years exp

Chase is seeking to expand its Asset and Wealth Management AI Engineering team by hiring a Senior Associate in Applied AI ML. This role involves hands-on development of machine learning and generative AI models, and deploying high-impact solutions in the financial services industry.

BankingFinancial Services

Responsibilities

Hands-on architecture and implementation of lighthouse ML and LLM-powered solutions

Close partnership with peers in a geographically dispersed team and colleagues across organizational lines

Collaborate across JPMorgan AWM’s lines of business and functions to accelerate adoption of common AI capabilities

Design and implement highly scalable and reliable data processing pipelines and deploy model inference services

Deploy solutions into public cloud infrastructure

Experiment, develop and productionize high quality machine learning models, services, and platforms to make a huge technology and business impact

Qualification

Machine Learning EngineeringPythonCloud Computing (AWS/Azure)LLM ExperienceData PipelinesData StructuresAlgorithmsNatural Language ProcessingMachine Learning FrameworksFinance KnowledgeCommunication

Required

MS in Computer Science, Statistics, Mathematics or Machine Learning

Minimum 4 years development experience, preferably with 2+ years hands-on Machine Learning Engineering

Proven capacity to innovate, including new AI/ML idea generation and GenAI-based solutions

Solid Python programming skills required; with other high-performance language such as Go a big plus

Expert knowledge of one of the cloud computing platforms preferred: Amazon Web Services (AWS), Azure, Kubernetes

Real-world experience in using LLMs (OpenAI, Claude or other models ) to solve business problems, including full workflow toolset, such as tracing, evaluations and guardrails. Understanding of LLM fine-tuning and inference a plus

Knowledge of data pipelines, both batch and real-time data processing on both SQL (such as Postgres) and NoSQL stores (such as OpenSearch and Redis)

Expertise in application, data, and infrastructure architecture disciplines

Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics

Excellent communication skills and ability to communicate with senior technical and business partners

Preferred

Expert in at least one of the following areas: Natural Language Processing, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis

Knowledge of machine learning frameworks: Pytorch, Keras, MXNet, Scikit-Learn

Understanding of finance or wealth management businesses is an added advantage