JPMorgan AI ML Director 

India, Karnataka, Bengaluru 

748557095

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)
• Strong understanding of AI implementation in software development and legacy code transformation.
• Familiarity with agentic workflows and relevant frameworks, such as LangChain, LangGraph,
• 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.
  using 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.