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求人JPMorgan Chase

Applied AI/ML Manager of Software Engineering

JPMorgan Chase

Applied AI/ML Manager of Software Engineering

JPMorgan Chase

New York, NY, United States, US

·

On-site

·

Full-time

·

2w ago

This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.

As a Manager of AI/ML Engineering team at JPMorgan Chase within the Business Banking , you lead our dynamic teams and will be responsible for applying advanced machine learning techniques to intricate task such as natural language processing, document screening and manage day-to-day implementation activities by identifying and escalating issues

Job responsibilities

  • Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, speech recognition and analytics, or recommendation systems
  • Choosing, extending, and innovating ML strategies for various banking problems
  • Provides guidance to immediate team of software engineers on daily tasks and activities
  • Sets the overall guidance and expectations for team output, practices, and collaboration
  • Anticipates dependencies with other teams to deliver products and applications in line with business requirements
  • Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
  • Learning about and understanding our supported businesses in order to drive practical and successful solutions

Required qualifications, capabilities, and skills

  • Formal training or certification in Software Engineering concepts and 5+ years applied experience and hand-on industry experience in Machine Learning.
  • Good understanding of the latest advancement of NLP concepts, such as the transformer architecture and knowledge distillation.
  • Experience in classical ML techniques including classification, clustering, optimization, cross validation, data wrangling, feature selection, and feature extraction
  • Experience leading technology projects
  • Experience managing technologists
  • Proficient in automation and continuous delivery methods
  • Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
  • Solid written and spoken communication skills
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines

Preferred qualifications, capabilities, and skills

  • Hands-on experience with virtual assistant model development and optimization
  • Familiarity with continuous integration models and unit test development
  • Experience with A/B experimentation and data/metric-driven product development

総閲覧数

1

応募クリック数

0

模擬応募者数

0

スクラップ

0

JPMorgan Chaseについて

JPMorgan Chase

JPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.

300,000+

従業員数

New York City

本社所在地

$500B

企業価値

レビュー

3.8

10件のレビュー

ワークライフバランス

3.2

報酬

4.1

企業文化

3.8

キャリア

3.0

経営陣

2.5

65%

友人に勧める

良い点

Good benefits and compensation

Supportive and collaborative environment

Flexible work arrangements

改善点

Long hours and heavy workload

Management issues and lack of direction

High stress during peak times

給与レンジ

41件のデータ

Mid/L4

Senior/L5

Mid/L4 · Applied AI ML Associate

2件のレポート

$188,500

年収総額

基本給

$145,000

ストック

-

ボーナス

-

$182,000

$195,000

面接体験

5件の面接

難易度

3.0

/ 5

期間

14-28週間

内定率

40%

体験

ポジティブ 20%

普通 80%

ネガティブ 0%

面接プロセス

1

Application Review

2

HireVue Video Interview

3

Recruiter Screen

4

Superday/Panel Interview

5

Final Interview

6

Offer

よくある質問

Behavioral/STAR

Technical Knowledge

Culture Fit

Past Experience

Case Study