Applied AI ML Lead at JPMC Candidate Experience page

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

15 Mar, 26

Salary

0.0

Posted On

15 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Software Engineering, Data Analysis, Python Development, Problem Solving, Collaboration, Communication, Generative AI, LLMs, Cloud Platforms, Feature Engineering, Model Evaluation, Mentoring, AI Applications, Scalability

Industry

Financial Services

Description

Out of the successful launch of Chase in 2021, we're a new team, with a new mission. We're creating products that solve real world problems and put customers at the center all in an environment that nurtures skills and helps you realize your potential. Our team is key to our sucess. We're value collaboration, curiosity and commitment. As an Applied AI ML Lead at JP Morgan Chase within the International Consumer Bank, you promote the integration of artificial intelligence in financial services and enhance business decision-making. You will be at the forefront of AI innovation, leveraging cutting-edge techniques and unique data assets to create AI-powered solutions that automate processes and improve operational efficiency. This role offers a unique blend of artificial intelligence, particularly in Machine Learning (ML), GenAI, and software engineering, allowing you to develop impactful products that transform business operations. In this position, you will leverage the latest advancements in LLMs, Machine Learning and artificial intelligence to design and implement AI applications that enhance decision-making and automate workflows. You will collaborate with cross-functional teams to create scalable AI solutions and effectively communicate the capabilities and benefits of AI to diverse audiences. Job Responsibilities Develop and implement advanced AI models, focusing on Machine Learning and LLM Agents, to tackle complex operational challenges. Evaluate and articulate the impact of AI-driven solutions, ensuring alignment with strategic business objectives. Architect and oversee the development of ML, GenAI applications and intelligent agents to automate and optimise software engineering processes. Collaborate with senior stakeholders to identify strategic business needs and translate them into comprehensive AI solutions. Analyse large datasets to extract actionable insights, supporting data-driven decision-making at a strategic level. Ensure the robustness, scalability, and security of AI applications in a production environment, focusing on long-term sustainability. Stay abreast of the latest advancements in AI technologies, and drive their integration into our operations. Mentor and guide junior team members, fostering a culture of innovation, collaboration, and continuous learning. Required qualifications, capabilities and skills Advanced degree in a STEM field, with significant experience in AI and Machine Learning applications. Proven track record of developing and implementing AI applications in a production environment with a focus on strategic impact and innovation. Deep familiarity with ML/AI frameworks and libraries, including Scikit-learn, PyTorch, Keras, Hugging Face and OpenAI. Extensive experience with generative AI models, particularly through cloud service APIs (e.g., OpenAI). Experience in integrating user feedback to create self-improving ML/AI applications. Strong understanding of data preprocessing, feature engineering, and evaluation techniques specific to ML/AI models. Excellent problem-solving skills with the ability to work both independently and collaboratively. Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders. Strong Python development skills, emphasising code quality, reliability, and comprehensive testing practices. Experience in software engineering practices. Preferred qualifications, capabilities and skills A Ph.D. is a plus but not required. Familiarity with cloud platforms (AWS) and their application to AI solutions. Experience in developing AI solutions using agentic frameworks. Experience fine-tuning LLMs with advanced techniques to enhance performance. Experience with prompt optimisation to improve the effectiveness of AI applications. Demonstrated ability to design and implement robust AI application architectures.

Responsibilities

Develop and implement advanced AI models to tackle operational challenges and enhance decision-making. Collaborate with cross-functional teams to create scalable AI solutions and communicate their benefits effectively.