Applied AI ML Lead

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 thatalign 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.

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