JPMorgan Sr Associate - Applied AI ML 

India, Karnataka, Bengaluru 

91389403

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• As a Machine Learning Scientist in the banking domain, you will be responsible for researching, developing, and implementing machine learning algorithms to solve complex problems related to personalized financial services in retail and digital banking domain. You will work closely with cross-functional teams to translate business requirements into technical solutions and drive innovation in our banking products and services.
• You will collaborate with product managers, key business stakeholders, engineering and platform partners to lead challenging projects that delivers cutting edge machine learning driven digital solutions. You will conduct research to develop state-of-the-art machine learning algorithms and models tailored to financial applications in personalization and recommendation space.
• You will design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results and productionize highly performant, scalable, trustworthy and often explainable solution.
• You will collaborate with data engineers and product analysts to preprocess and analyse large datasets from multiple sources. You will stay up-to-date with latest publications in relevant Machine Learning domains and will be responsible for finding applications for the same in your problem spaces for improved outcomes. You will communicate findings and insights to stakeholders through presentations, reports, and visualizations.
• You will work with regulatory and compliance teams to ensure that machine learning models adhere to standards and regulations. You will mentor Junior Machine Learning associates in delivering successful projects and building successful career in the firm.You will also participate and contribute back to firmwide Machine Learning communities through patenting, publications and speaking engagements.

Required qualifications, capabilities, and skills

• MS or PhD degree in Computer Science, Statistics, Mathematics or Machine learning related field.
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficient in coding in one or more languages
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Overall knowledge of the Software Development Life Cycle
• 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.
• 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

• 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 EM. Experience with large scale training, validation and testing experiments.
• Experience with cloud Machine Learning services in AWS like Sagemaker. Experience with Container technology like Docker, ECS etc.
• Experience with Kubernetes based platform for Training or Inferencing. Contributions to open-source ML projects can be a plus.
• Participation in ML competitions (e.g., Kaggle) and hackathons demonstrating practical skills and problem-solving abilities. Understanding of how ML can be applied to various domains like healthcare, finance, robotics, etc.