Job 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 3+ years of experience as an Engineering Manager leading ML teams 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 atleast 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.