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Machine Learning Engineer at JPMC Candidate Experience page
Jersey City, New Jersey, United States -
Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

0.0

Posted On

04 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Data Processing, Python, Java, Data Structures, Algorithms, Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Data Mining, Statistics, Tensorflow, Pytorch, Cloud Technologies, ETL Data Pipelines

Industry

Financial Services

Description
Responsibilities Collaborate with all of JPMorgan’s lines of business and functions to delivery software solutions. Experiment, develop and productionize high quality machine learning models, services and platforms to make huge technology and business impact. Design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to drive and optimize business result. Required Qualification BE/B. Tech, ME/MS or PhD degree in Computer Science, Statistics, Mathematics or Machine learning related field. Solid programming skills with Python/Java or other equivalent languages. Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Expert in at least one of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Knowledge of machine learning frameworks: Tensorflow/Pytorch Knowledge of prompt engineering. Experience in ETL data pipelines both batch and real-time data processing, Data warehousing, NoSQL DB, Elastic. Cloud Technologies: AWS/GCP/Azure, Kubernetes Strong analytical and critical thinking skills. Self-motivation, great communication skills and team player.
Responsibilities
Collaborate with various lines of business to deliver software solutions and develop high-quality machine learning models. Design and implement scalable data processing pipelines to optimize business results.