Applied AI ML Senior Associate

JPMorgan Chase & Co.; Bengaluru; On-site; INR 3,200,000 - 5,200,000; Full time

Job summary

JPMorgan Chase & Co. in Bengaluru seeks a senior Data Scientist to lead development and deployment of innovative AI/ML solutions within the Chief Administrative Office. You will collaborate with product, engineering, and business teams to deliver scalable, production-ready systems while ensuring responsible AI governance.

You will mentor other AI engineers, drive modern ML practices, and work with cutting-edge technologies to accelerate the organization's data-driven initiatives.

Qualifications

• Master’s or PhD in CS/Engineering/Math or related quantitative field.
• 6+ years hands-on ML experience including generative AI/LLMs.
• Proficiency in Python; ML frameworks like PyTorch or TensorFlow.
• Proven experience designing, training, and deploying large-scale ML models in production.
• Deep understanding of prompt engineering and orchestration frameworks.
• Experience with cloud platforms (AWS/Azure/GCP) and distributed systems (Kubernetes, Ray, Slurm).
• Proficiency with MLOps tools (MLflow, model monitoring, ML CI/CD).
• Strong communication skills for technical and business audiences.
• Demonstrated leadership in cross-functional teams.
• Experience applying data science/ML to business problems.
• Experience with high-performance computing or GPU infrastructure, big data tools, RL/meta learning, search/ranking, or recommender systems.
• Domain knowledge in financial services or regulated industries.
• Experience deploying ML on cloud platforms like AWS SageMaker, EKS; contributions to GenAI/LLM projects.

Responsibilities

• Lead design, development, and deployment of advanced AI, GenAI, and LLM solutions.
• Serve as SME on a wide range of ML techniques and optimizations.
• Collaborate with product, engineering, and business teams to deliver scalable, production-ready AI systems.
• Run experiments with the latest ML tech, analyze results, and tune models for performance.
• Own end-to-end Python code development for PoC and production-ready solutions.
• Integrate generative AI within the ML platform using state-of-the-art techniques.
• Drive adoption of modern ML infrastructure, tools, and best practices.
• Optimize system accuracy and performance by identifying inefficiencies.
• Communicate technical concepts to tech and business stakeholders.
• Ensure responsible AI practices, governance, and regulatory compliance.
• Mentor and guide other AI engineers and scientists.

Skills

Leadership

Communication

Business-focused analytics

Prompt engineering

GenAI/LLM experiences

Reinforcement learning

Search/ranking

Graph techniques

Education

Master’s or PhD in Computer Science/Engineering/Math

6+ years ML experience

Tools

Python

PyTorch

TensorFlow

AWS

Azure

GCP

Kubernetes

Ray

Slurm

MLflow

CI/CD for ML

Model monitoring

AWS SageMaker

EKS

Job description

Join a world-class data science team at JPMorgan Chase and help shape the future of our Chief Administrative Office.

As a Data Scientist Senior Associate in the Chief Data & Analytics Office, you will lead the development and deployment of innovative AI and machine learning solutions. You will collaborate with cross-functional teams to address complex business challenges, drive adoption of modern ML practices, and ensure responsible AI governance. You will have the opportunity to work withstate-of-the-arttechnologies and contribute to a culture of technical excellence and continuous learning. We value curiosity, technical excellence, and a passion for solving complex problems. Ifyou’reready to accelerate your career and drive meaningful change, we want to hear from you.

Job responsibilities:

• Lead the hands-on design, development, and deployment of advanced AI, GenAI, and large language model solutions.
• Serve as a subject matter expert on a wide range of machine learning techniques and optimizations.
• Collaborate with product, engineering, and business teams to deliver scalable, production-ready AI systems.
• Conduct experiments using the latest ML technologies, analyze results, and tune models foroptimalperformance.
• Own end-to-end code development in Python for both proof-of-concept and production-ready solutions.
• Integrate generative AI within the ML platform usingstate-of-the-arttechniques.
• Drive adoption of modern ML infrastructure, tools, and best practices.
• Optimizesystem accuracy and performance byidentifyingand resolving inefficiencies.
• Communicate technical concepts and results to both technical and business stakeholders.
• Ensure responsible AI practices, model governance, and compliance with regulatory standards.
• Mentor and guide other AI engineers and scientists, fostering a culture of continuous learning.

Required qualifications, capabilities, and skills:

• Master’s or PhD in Computer Science, Engineering, Mathematics, or a related quantitative field.
• Minimum 6 years of hands-on experience in applied machine learning, including generative AI, large language models, or foundation models.
• Experience programming in Python; experience with ML frameworks such asPyTorchor TensorFlow.
• Proven experience designing, training, and deploying large-scale ML/AI models in production environments.
• Deep understanding of prompt engineering, agentic workflows, and orchestration frameworks.
• Experience with cloud platforms (AWS, Azure, GCP) and distributed systems (Kubernetes, Ray,Slurm).
• Solid grasp ofMLOpstools and practices (MLflow, model monitoring, CI/CD for ML).
• Strong communicationskills with the ability to explain complex technical concepts to diverse audiences.
• Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.
• Experience applying data science and ML techniques to solve business problems and passion for detail, follow-through, and technical excellence.

Preferred qualifications, capabilities, and skills:

• Experience with high-performance computing and GPU infrastructure (e.g., NVIDIA DCGM, Triton Inference).
• Familiarity with big data processing tools and cloud data services.
• Advanced knowledge in reinforcement learning, meta learning, or related advanced ML areas.
• Experience with search/ranking, recommender systems, or graph techniques.
• Background in financial services or regulated industries.
• Experience withbuilding and deploying ML models on cloud platforms such as AWSSagemaker, EKS, etc.
• Published research or contributions to open-source GenAI/LLM projects.