Applied AI ML Lead -Digital

Role overview

Applied AI ML Lead -Digital at JP Morgan

Responsibilities

• You will experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant impact on technology and business.
• Collaborate with product managers, key business stakeholders, engineering, and platform partners to lead challenging projects that deliver cutting-edge machine learning-driven digital solutions.
• Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results, and productionize highly performant, scalable, trustworthy, and often explainable solutions.
• Collaborate with data engineers and product analysts to preprocess and analyze large datasets from multiple sources.
• Work with regulatory and compliance teams to ensure that machine learning models adhere to standards and regulations.
• Contribute to a transformative journey and make a substantial impact on a wide range of customer products.

Required qualifications

• Required qualifications, capabilities and skills 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, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.

Preferred qualifications and skills

• 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.

Employment details

• Location: Bengaluru [Karnataka] [India]

Additional role details

• We're seeking top talents for our AI engineering team to develop high-quality machine learning models, services, and scalable data processing pipelines.
• Candidates should have a strong computer science background and be ready to handle end-to-end projects, focusing on engineering.
• As an Applied AI ML Lead within the Digital Intelligence team at JPMorgan, you will collaborate with all lines of business and functions to deliver software solutions.
• Additionally, you will design and implement highly scalable and reliable data processing pipelines, and perform analysis and insights to promote and optimize business results.
• Job Responsibilities Research, develop, and implement 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.
• Conduct research to develop state-of-the-art machine learning algorithms and models tailored to financial applications in personalization and recommendation spaces.
• 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.
• Mentor Junior Machine Learning associates 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.
• 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 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.
• 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 and Container technology like Docker, ECS etc.
• Experience with Kubernetes based platform for Training or Inferencing.