Applied AI ML Engineer Lead
JPMorgan
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This role on the market
1,446 open applied roles across 187 companies are on ApplySarthi right now, most of them in Bengaluru (93), Hyderabad (15), Delhi NCR (8).
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- Senior Applied Research Scientist - PersonalizationSpotify
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- Principal Applied ScientistJobgether
What applied roles keep asking for: Python (63%), Machine learning (47%), LLMs (38%), Java (31%), C++ (30%), Deep learning (23%), AWS (22%), Generative AI (18%) — counted across their open postings here.
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Counted across 14 company job boards, updated as roles open and close.
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Interviews for applied roles keep coming back to Python, Machine learning, LLMs, Java. Practise those questions before you sit with JPMorgan.
Questions you are likely to be asked
- Why do you want to join JPMorgan?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
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Practise the Applied AI ML Engineer Lead at JPMorgan interview free →Our goal is to build the next generation of AI: autonomous agents that can reason, plan, act, and learn to solve critical problems for an industry leading financial institution. We are looking for architects who will define the future of banking through Agentic AI. The Applied Artificial Intelligence and Machine Learning team in Commercial and Investment Banking is transforming operations by leveraging the latest advancements in agentic AI and frontier models. As an Applied Artificial Intelligence and Machine Learning Lead at JPMorganChase within the Applied AI Research team in Commercial and Investment Banking , you will help build autonomous agent systems that can reason, plan, act, and learn to solve high-impact business problems. You will bridge cutting-edge research and enterprise-grade delivery, shaping how applied AI is designed, evaluated, and deployed at scale. You will partner closely with business and technology stakeholders to translate priority needs into measurable outcomes, while raising engineering and scientific standards across the team. Job Responsibilities Architect and deliver generative artificial intelligence and agent-based solutions that automate complex operational workflows end-to-end Translate priority business problems into research and engineering plans, success metrics, and scalable solution designs Build multi-agent systems that collaborate reliably, coordinate tasks, and improve over time through feedback and evaluation Design reusable services, libraries, and reference architectures that accelerate adoption across applied AI teams Establish rigorous experimentation practices, including offline/online evaluation, ablation testing, and error analysis, to drive measurable improvements Mentor and develop applied AI engineers and researchers, fostering a culture of scientific rigor, ownership, and continuous learning Partner with stakeholders across business and technology teams to scale solutions responsibly, balancing performance, reliability, and security Required Qualifications, Capabilities, and Skills Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience Advanced degree (Master’s or Doctorate) in Computer Science, Machine Learning, Statistics, or a related quantitative field Demonstrated experience designing experiments and evaluations for machine learning systems, including clear metrics and reproducible results Proven track record deploying machine learning applications into production environments with operational excellence (monitoring, reliability, and lifecycle management) Strong software engineering skills in modern programming languages and machine learning frameworks, with experience building reusable components Experience with distributed computing patterns for training and serving, and with state management for agent workflows Ability to lead through influence across cross-functional teams, translating complex technical topics for varied audiences Preferred Qualifications, Capabilities, and Skills Experience building and evaluating autonomous agent systems (planning, tool-use, orchestration, and multi-agent coordination) Experience with cloud-based machine learning platforms, such as Amazon Web Services (AWS) SageMaker or Amazon Bedrock Publications, open-source contributions, or other evidence of applied research impact in machine learning or generative artificial intelligence Familiarity with financial services domains and operational processes, including risk-aware design and production constraints FEDERAL DEPOSIT INSURANCE ACT: This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries. #LI-RB3 #CIBAppliedAI
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Listed on oraclehcm · posted 2026-08-27. ApplySarthi collects openings and links to application pages; the role is advertised by JPMorgan, not by us.