Us Ai & Data Policy Director - Executive jobs at Jpmorgan in United States, Washington

• Serves as a subject matter expert on a wide range of ML techniques and optimizations.
• Provides in-depth knowledge of ML algorithms, frameworks, and techniques.
• Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
• Conducts experiments using latest ML technologies, analyzing results, tuning models
• Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions.
• Optimizes system accuracy and performance by identifying and resolving inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions.
• Integrates Generative AI within the ML Platform using state-of-the-art techniques.

• MS and/or PhD in Computer Science, Machine Learning, or a related field, with at least 2 years of applied machine learning experience.
• At least 4 years' experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must.
• At least 2 years’ experience in applying data science, ML techniques to solve business problems.
• Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs)
• Hands-on experience with machine learning and deep learning methods.
• Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow.
• Experience in advanced applied ML areas such as GPU optimization, fine tuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search).
• Ability to work on tasks and projects through to completion with limited supervision.
• Passion for detail and follow through. Excellent communication skills and team player.

• Master’s degree in computer science, ML or related areas
• Experience with Ray, MLFlow, and/or other distributed training frameworks.
• In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
• Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
• Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.
• Experience working with large-scale MLOps pipelines, working with and deploying models to production services.

At Compliance Conduct and Operational Risk division, as a trade surveillance personnel you would be responsible for identifying potential instances of market abuse, notably insider trading and market manipulation using well known surveillance systems, conducting surveillance of activities in Firm and Employee accounts to comply with the information barrier and restricted list policies. The trade surveillance team would be responsible for looking into the risks across markets using the established surveillance program to safeguard the firm against any reputational and/or financial risk while complying with internal policies and regulatory requirements.

Job Responsibilities:

• Reviewing Trade surveillance alerts and conducting analysis of trading and market activity for asset class and programs such as Equities, Information barriers, Fixed income, Futures/ Options and Asset management
• Properly documenting the review and disposition of the exceptions as well as escalating matters appropriately
• Working with business and compliance stakeholders to identify potential market misconduct and technical rule violations and disposition, accordingly, include through interaction with regional Surveillance teams
• Conducting alert-based reviews for potential violations of laws, rules, and regulations.
• Work along with peers, handle multiple reports, engage in result-oriented tasks in a fast-paced environment. Identifying areas for process improvement and contribute towards the same
• Additional duties as assigned & Identifying areas for process improvement and contribute towards the same
• Identify key issues, risks, trends, observations and have them highlighted to management/key stakeholders

Required qualifications, capabilities, and skills:

• Qualified graduate with minimum of 6 years of trade surveillance / product experience with exchange traded products (including equities, futures and Fixed income) and/or information barriers / Asset management
• An understanding of markets and potential market manipulative behavior and a demonstrated ability to conduct reviews relating to regional rules and regulations
• Experience with reviewing trading activity for Compliance and familiarity with securities laws and regulations for identifying potential trading violations

Preferred Qualifications, Capabilities, and Skills:

• Experience with SMARTS, Actimize or similar Trade surveillance systems is a plus
• Experience with navigation and sourcing of information in Bloomberg/public sources
• Working Knowledge of securities markets preferred

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Deliver AI/ML based solutions to improve Kubernetes platforms for JPMC
• Regularly provides technical guidance and direction to support the business and its technical teams

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience
• Experience applying data engineering and machine learning techniques
• Experience in Generative AI, LLMs and AI Agents

• Experience working with modern private & public cloud infrastructure platforms - Kubernetes, AWS EKS Terraform, Ansible and other automation tools.
• Experience in multiple Cloud platforms like GCP GKE is a plus
• Knowledge of deep learning and ML Ops workflows
• Experience in Time Series analysis, including forecasting, anomaly detection, and trend analysis

As a
Applied AI ML Sr Associate at JPMorgan Chase within the Corporate Sector – AIML Data Platforms,you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery.

You will be responsible for hiring, leading, and mentoring a team of Machine Learning and Software Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable ML solutions with operational excellence. You will engage deeply in technical aspects, reviewing code, mentoring engineers, troubleshooting production ML applications, and enabling new ideas through rapid prototyping. Your passion for parallel distributed computing, big data, cloud engineering, micro-services, automation, and operational excellence will be key.

Job Responsibilities

• Architect and implement distributed AI/ML infrastructure, including inference, training, scheduling, orchestration, and storage.
• Integrate Generative AI and Classical AI within the ML Platform using state-of-the-art techniques.
• Implement, deliver, and support high-quality ML solutions in partnership with a team of ML Engineers.
• Collaborate with product teams to deliver tailored, AI/ML-driven technology solutions.
• Develop advanced monitoring and management tools for high reliability and scalability in AI/ML systems.
• Optimize AI/ML system performance by identifying and resolving inefficiencies and bottlenecks.
• Drive the adoption and execution of AI/ML Platform tools across various teams.
• Lead the entire AI/ML product life cycle through planning, execution, and future development by continuously adapting, developing new AI/ML products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth.

Required Qualifications, Capabilities, and Skills

• Bachelor's degree or equivalent practical experience in a related field.
• 6+ years of experience in engineering management with a strong technical background in machine learning.
• Extensive hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn).
• Deep expertise in Cloud Engineering (AWS, Azure, GCP) and Distributed Micro-service architecture.
• Experienced with Kubernetes ecosystem, including EKS, Helm, and custom operators.
• Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems.
• Strategic thinker with the ability to craft and drive a technical vision for maximum business impact.

Preferred Qualifications, Capabilities, and Skills

• Strong coding skills and experience in developing large-scale AI/ML systems.
• Proven track record in contributing to and optimizing open-source ML frameworks.
• Understanding & experience of AI/ML Platforms, LLMs, GenAI, and AI Agents.

As a
Applied AI ML Lead at JPMorgan Chase within the Corporate Sector – AIML Data Platforms, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery.

You will be responsible for hiring, leading, and mentoring a team of Machine Learning and Software Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable ML solutions with operational excellence. You will engage deeply in technical aspects, reviewing code, mentoring engineers, troubleshooting production ML applications, and enabling new ideas through rapid prototyping. Your passion for parallel distributed computing, big data, cloud engineering, micro-services, automation, and operational excellence will be key.

Job Responsibilities

• Lead and manage a team of machine learning engineers, ensuring the implementation, delivery, and support of high-quality ML solutions.
• Collaborate with product teams to deliver tailored, AI/ML-driven technology solutions.
• Architect and implement distributed AI/ML infrastructure, including inference, training, scheduling, orchestration, and storage.
• Develop advanced monitoring and management tools for high reliability and scalability in AI/ML systems.
• Optimize AI/ML system performance by identifying and resolving inefficiencies and bottlenecks.
• Drive the adoption and execution of AI/ML Platform tools across various teams.
• Integrate Generative AI and Classical AI within the ML Platform using state-of-the-art techniques.
• Lead the entire AI/ML product life cycle through planning, execution, and future development by continuously adapting, developing new AI/ML products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth.
• Manage, mentor, and develop a team of AI/ML professionals in a way that promotes a culture of excellence, continuous learning, and supports their professional goals.

Required Qualifications, Capabilities, and Skills

• Bachelor's degree or equivalent practical experience in a related field.
• 8+ years of experience in engineering management with a strong technical background in machine learning.
• Extensive hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn).
• Deep expertise in Cloud Engineering (AWS, Azure, GCP) and Distributed Micro-service architecture.
• Experienced with Kubernetes ecosystem, including EKS, Helm, and custom operators.
• Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems.
• Strategic thinker with the ability to craft and drive a technical vision for maximum business impact.
• Demonstrated leadership in working effectively with engineers, data scientists, and ML practitioners.

Preferred Qualifications, Capabilities, and Skills

• Strong coding skills and experience in developing large-scale AI/ML systems.
• Proven track record in contributing to and optimizing open-source ML frameworks.
• Recognized thought leader within the field of machine learning.
• Understanding & experience of AI/ML Platforms, LLMs, GenAI, and AI Agents.