Applied AI ML Lead at JPMC Candidate Experience page

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

06 May, 26

Salary

0.0

Posted On

05 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Team Management, Model Production, Natural Language Processing, Graph Learning, Reinforcement Learning, Ranking and Recommendation, Data Structures, Algorithms, Data Mining, Statistics, Tensorflow, Pytorch, Python, Spark, Cloud Services

Industry

Financial Services

Description

We're seeking top talents for our AI engineering team to develop high-quality machine learning models, services, and scalable data processing pipelines. Candidate should have a strong Machine Learning background with experience in managing a team of machine learning engineers and focus on taking ML models to production. As an Applied AI ML Lead within the Digital Intelligence team at JPMorgan, you will lead a team of ML engineers with focus on all aspects of ML architecture, infra selection, model training, fine-tuning, ablation studies, and productization. This role requires strong technical expertise, leadership skills, and the ability to collaborate across teams. The ideal candidate has a proven track record in managing teams, delivering production grade ML models across cloud and on-device environment, and making informed decisions that align with business objectives and deliver tangible value. Job Responsibilities Research and develop machine learning algorithms to solve complex problems related to personalized financial services in retail and digital banking domains. Work closely with cross-functional teams to translate business requirements into technical solutions and drive innovation in banking products and services. Collaborate with product managers, key business stakeholders, engineering, and platform partners to lead challenging projects that deliver cutting-edge machine learning-driven digital solutions. Stay up-to-date with the latest publications in relevant Machine Learning domains and find applications for the same in your problem spaces for improved outcomes. Communicate findings and insights to stakeholders through presentations, reports, and visualizations. Work with regulatory and compliance teams to ensure that machine learning models adhere to standards and regulations. Mentor juniors in delivering successful projects and building successful careers in the firm. Participate and contribute back to firm-wide Machine Learning communities through patenting, publications, and speaking engagements. Required qualifications, capabilities and skills Minimum of 5+ years of experience as an ML Engineer/Lead MS or PhD degree in Computer Science, Statistics, Mathematics or Machine learning related field. Expert in at least one of the following areas: Natural Language Processing, Graph Learning, Reinforcement Learning, Ranking and Recommendation Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn. Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc. Strong analytical and critical thinking skills for problem solving. Excellent written and oral communication along with demonstrated teamwork skills. Demonstrated ability to clearly communicate complex technical concepts to both technical and non-technical audiences Experience in working in interdisciplinary teams and collaborating with other researchers, engineers, and stakeholders. A strong desire to stay updated with the latest advancements in the field and continuously improve one's skills Preferred qualifications, capabilities and skills 8 (MS) or 5 (PhD) years of relevant experience, with at least 3 years in leadership roles. Deep hands-on experience with real-world ML projects, either through academic research, internships, or industry roles. Experience with distributed data/feature engineering using popular cloud services like AWS EMR Experience with large scale training, validation and testing experiments. Experience with cloud Machine Learning services in AWS like Sagemaker. 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 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. Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

Responsibilities

Lead a team of ML engineers to develop machine learning algorithms for personalized financial services. Collaborate with cross-functional teams to translate business requirements into technical solutions and drive innovation.