Applied Aiml Director Genai jobs at Jpmorgan in United States, Seattle

• 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.

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.

DESCRIPTION:

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Applied Statistics, Mathematics, Operations Research, Optimization, Data Science, or related field of study plus 3 years (36 months) of experience in the job offered or as Applied Artificial Intelligence / Machine Learning, Machine Learning Engineer, Research Scientist, or related occupation. The employer will alternatively accept a PhD in Applied Statistics, Mathematics, Operations Research, Optimization, Data Science, or related field of study plus 1 year (12 months) of experience in the job offered or as Applied Artificial Intelligence / Machine Learning, Machine Learning Engineer, Research Scientist, or related occupation.

Skills Required: This position requires experience with the following: At least one of the following: personalization, recommendation, speech recognition, or NLP; designing machine learning experiments and frameworks including feature extraction, data augmentation, synthetic data generation, model pre- training, fine-tuning, performance evaluation, robustness testing, interpretability analysis and visualization; outlining and evaluating intrinsic and extrinsic metrics for model performance aligned with business goals; big data and scalable model training; personalized contents, recommender systems, search, and ranking; A/B testing experimentation and data-driven product development; cloud-native deployment in a large scale distributed environment; experience in either: reinforcement Learning or Meta Learning; developing and debugging production-quality code; continuous integration models and unit test development; machine learning and deep learning toolkits including NLTK, spaCy, Hugging Face transformers, Scikit-Learn, Rasa NLU, PyTorch, Docker, Numpy, Pandas, Spark, MongoDB, Scala; experience with machine learning and deep learning.

Job Location: 1201 3rd Ave, Seattle, WA 98101.

Full-Time. Salary: $210,000 - $260,000 per year.

Job responsibilities• Leads the development of innovative API products tailored for high-value customers, ensuring alignment with business objectives and customer needs.
• Drives end-to-end project development for new API initiatives, fostering a culture of innovation and excellence within the team.
• Makes decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
• Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
• Delivers technical solutions that can be leveraged across multiple businesses and domains
• Influences peer leaders and senior stakeholders across the business, product, and technology teams
• Champions the firm’s culture of diversity, opportunity, inclusion, and respectRequired qualifications, capabilities, and skills• Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
• Proven experience in designing and implementing REST and GraphQL APIs, with a strong understanding of best practices and standards.
• In-depth experience with one or more API Gateways, demonstrating the ability to manage and optimize API traffic and security.
• Proficient knowledge and hands-on experience with React UI development, showcasing the ability to build and maintain scalable and efficient user interfaces.
• Demonstrated ability to collaborate and influence across organizational boundaries, fostering strong partnerships and driving alignment on strategic initiatives.
• Strong strategic thinking and team leadership skills, with a track record of guiding teams to achieve complex objectives and deliver impactful solutions.
• Experience developing or leading cross-functional teams of technologists
• Practical cloud native experience
• Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field

Preferred Qualifications

• Experience managing API security including key exchange, encryption and signature and DDoS protection

Job Description

Elevate your career as the Applied AIML Director of GenAI, where your technical expertise and visionary leadership will shape the future of AI and ML solutions.

As an Executive Director within the Applied AI/ML, Agent Builder Platform team, you will collaborate with diverse teams to develop and implement the Agent SDK and Specialized agents for AIT. You will be actively engaged in our innovative projects, steering the advancement of Agentic Systems within the firm.

Job responsibilities

• Define and drive the long term vision for agentic AI development: Includes strategic opportunities for agentic AI within the organization and setting the direction for research and development efforts.
• Lead and manage a team of AI researchers and engineers: this involves hiring, mentoring, and providing technical guidance to the team.
• Translate AI advancements into practical, scalable solutions: You will be responsible for taking research prototypes and turning them into robust, production-ready applications.
• Oversee the development and deployment of agentic AI systems: This includes ensuring the quality, performance, and reliability of the AI Systems as well as their ethical and responsible development.
• Collaborate with other teams and stakeholders: you will work closely with product management, engineering, and business teams to aligh AI initiatives with overall business objectives..

Required Qualifications, Capabilities, and Skills

• 10+ years of experience in engineering management with a strong technical background.
• Extensive hands-on experience with ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn).
• Deep expertise in AWS / GCP and Kubernetes ecosystem, including EKS, Helm, and custom operators.
• Strong coding skills and experience in developing large-scale ML systems.
• Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems.
• Proven track record in contributing to and optimizing open-source ML frameworks.
• 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.
• Proven ability to identify trade-offs, clarify project ambiguities, and drive decision-making.

Job responsibilities

• Leads multiple technology and process implementations across departments to achieve firmwide technology objectives
• Directly manages multiple areas with strategic transactional focus
• Provides leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business
• Acts as the primary interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives
• Manages multiple stakeholders, complex projects, and large cross-product collaborations
• Influences peer leaders and senior stakeholders across the business, product, and technology teams
• Champions the firm’s culture of diversity, equity, inclusion, and respect
• Lead the development of AI/ML-centered EKS, Ray, EMR, Notebooks, and Studios that are tailored towards data scientists and ML/AI engineers.
• Act as a primary engineering leader with third-party stakeholders and internal stakeholders.
• Elevate the overall engineering culture and practices across the organization and the firm.
• Represent the organization through external and internal talks and conferences.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
• Experience developing or leading large or cross-functional teams of technologists
• Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
• Experience leading complex projects supporting system design, testing, and operational stability
• Experience with hiring, developing, and recognizing talent
• Extensive practical cloud native experience
• Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
• Bachelor's degree in Computer Science or equivalent practical experience.
• 5 years of experience working with Machine Learning, AI, Large Language Models (LLM) infrastructure, especially with training, model development, and other requests.
• Experience operating in a hyper-growth entrepreneurial environment, scaling new and emerging products from the ground up.

Preferred qualifications, capabilities, and skills

• Experience working at code level
• M.Sc or Ph.D in CS or any related field.
• Expertise in Machine Learning frameworks like Python, Scikit-learn, PyTorch, TensorFlow, Apache Spark, and experience with Generative AI models like GANs, Transformers, and Diffusion Models.
• Knowledge of MLOps best practices around model training, evaluation, deployment, and governance. Ability to communicate and help clients operationally set up MLOps functions.
• Experience integrating ML solutions with cloud platforms like AWS SageMaker, GCP Vertex AI, Azure Cognitive Services, and leveraging their pre-built capabilities.
• Proficiency in ML workflow tools like Kubeflow and MLflow for experiment tracking, model management, and model serving.
• Ability to identify and articulate the business value of AI/ML to stakeholders using innovative techniques like AI Readers, AI Assistants, Agentic frameworks, etc.
• Strong communication, presentation, and storytelling skills to influence technical sales cycles with business decision-makers.
• Passion for AI/ML and ability to stay updated on the latest advancements through conferences, publications, cohorts, etc. Experience in consulting, sales engineering, and/or customer success.
• Comfortable in evangelizing and marketing ML/AI practice with internal teams, partners, and customers alike.