דרושים Morgan Health - Care Innovation Data ב-גיי פי מורגן ב-United States, Washington

Job responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• Drive innovation in machine learning solutions, ensuring scalability, flexibility, and future-proof architecture
• Act as a thought leader and trusted advisor to executive leadership, providing strategic recommendations on machine learning initiatives and solutions
• Architect and oversee the development of next-generation machine learning models and systems leveraging cutting-edge technologies
• Ensure the platform supports complex use cases, including real-time predictions, big data processing, and advanced analytics
• Promote software and model quality, integrity, and security across the organization

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Proven track record of building and scaling software and or machine learning platforms in high-growth or enterprise environments
• 10 plus years of hands-on experience and expertise in software development frameworks and tools such as Java, Python and JavaScript
• Deep understanding of distributed systems, cloud-native architectures, and modern machine learning technologies
• Experience in cloud platforms such as AWS, GCP, or Azure
• Knowledgeable in machine learning frameworks, ML Ops tools and practices
• Strong proficiency in engineering programming languages (e.g., Python, Java) and infrastructure as code (e.g., Terraform, CloudFormation)
• Proficient in building AI Agents (e.g., LangChain, LangGraph, AutoGen), integration of tools (e.g., API) and RAG based solutions (e.g., open search)
• Hands-on experience with software development pipeline and orchestration tools (e.g., Jenkins, GitLab CI/CD)
• Exceptional ability to communicate complex technical concepts to both technical and non-technical audiences

• Hands-on experience with big data, pipeline, orchestration tools and real-time processing frameworks

• Experience working at the code level, with a strong understanding of software development practices
• Certified as AWS Solutions Architect, Certified Developer, or similar certification

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.