Principal Architect
at J.P. Morgan
Posted 14 days ago
No clicks
- Compensation
- Not specified
- City
- Hyderabad
- Country
- India
Currency: Not specified
Senior architect role leading AIML, Generative AI and enterprise data platform architecture within Consumer and Community Banking. Responsible for designing and evangelizing scalable ML/GenAI platforms, mentoring engineers, and collaborating with product and engineering teams to move experiments into production. Hands-on development in Python/Java and deep involvement in ML techniques (NLP, LLMs), distributed training/serving, and evaluation/feedback loops. Focuses on governance, performance optimization, and driving technical decisions across projects.
Location: Hyderabad, Telangana, India
You are a trailblazer, leading the way in a specific area of architecture and making a profound impact on the people, technologies, and projects across departments. With your impressive experience steering multiple complex projects forward, the entire firm will reach new levels of success.
Job responsibilities
- Owns and evangelizes solutions related to data architecture, ML Platform as well as GenAI platform architecture, provide tactical solution and design support to the team and embedded with engineering on the execution and implementation of processes and procedures
- Owns governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
- Serve as a subject matter expert on a wide range of ML techniques and optimizations.
- Provide in-depth knowledge of distributed ML platform deployment including training and serving.
- Create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques.
- Gain Experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines.
- Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team.
- Owning end to end code development in python/Java for both proof of concept/experimentation and production-ready solutions.
- Optimizing 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.
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Drives decisions that influence the product design, application functionality, and technical operations and processes.
- Formal training or certification in 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
- At least 10 years experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must.
- Solid understanding of using ML techniques specially in Natural Language Processing (NLP) and Large Language Models (LLMs)
- Hands-on experience with machine learning and deep learning methods.
- Good understanding in deep learning frameworks such as PyTorch or TensorFlow.
- Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search).
- Ability to work on system design from ideation through completion with limited supervision.
- Passion for detail and follow through. Excellent communication skills and team player.
- Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.
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Practical cloud native experience such as AWS.
Preferred qualifications, capabilities, and skills
- MS and/or PhD in Computer Science, Machine Learning, or a related field
- Experience with Ray, MLFlow, and/or other distributed training frameworks.
- In-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
- Advanced knowledge in Reinforcement Learning or Meta Learning.
- 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.
