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JPMorgan Applied AI ML Director India, Karnataka, Bengaluru 275704890
08.04.2025
Job responsibilities
- Establish and promote a library of common ML assets, including reusable ML models, features stores, data pipelines, and standardized templates.
- Lead efforts to create shared tools and platforms that streamline the end-to-end ML lifecycle across the organization.
- 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
- Advise on the strategy and development of multiple products, applications, and technologies.
- Lead advisor on the technical feasibility and business need for AIML use cases.
- Liaise with firm wide AI ML stakeholders.
- Translate highly complex technical issues, trends, and approaches to leadership to drive the firm's innovation and enable leaders to make strategic, well informed decisions about technology advancements.
- Influence across business, product and technology teams and successfully manages senior stakeholder relationships.
- champion the firm's culture of diversity, opportunity, inclusion, and respect.
Required qualifications, capabilities, and skills
- Formal training or certification on Machine Learning concepts and 10+ years applied experience in one of the programming languages like Python, Java, C/C++, etc. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
- MS and/or PhD in Computer Science, Machine Learning, or a related field
- 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.
- Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team.
- 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. Practical cloud native experience such as AWS needed.
Preferred qualifications, capabilities, and skills
- Experience with Ray, MLFlow, and/or other distributed training frameworks.
- Understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
usingAdvanced 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.
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