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Applied AI ML Lead - ML assisted Surveillance

at J.P. Morgan

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted a month ago

No clicks

Compensation: Not specified
City: Bengaluru
Country: India

Lead and coach engineering teams to deliver cloud-native, ML-powered surveillance products with a strong focus on quality, operational readiness, and compliance. Own end-to-end delivery of the product roadmap, drive DevOps and SRE practices, and productionize ML/LLM-based detection and alerting features with feedback loops for model improvement. Collaborate cross-functionally with Product, Compliance, Data Science, Architecture, and SRE teams to ensure architectural consistency, risk mitigation, and operational excellence.

Location: Bengaluru, Karnataka, India

We have an exciting opportunity for you to advance your engineering leadership career and drive innovation in ML-powered solutions.

As an Applied AI ML Lead in the Surveillance Product Team, you will guide and coach teams to deliver high-quality, cloud-native, ML-powered business applications. You will foster a culture of engineering excellence and compliance, collaborating across functions to achieve strategic goals.

Job responsibilities

Coach teams on design rigor, testing strategies, and SRE mindset to ensure operational readiness.

Drive a culture of ownership, engineering excellence, and compliance-first thinking.

Own end-to-end delivery of the product roadmap through Agile planning and risk mitigation.

Build and productionize ML and LLM-based detection and alerting features, ensuring feedback loops for model improvement.

Partner with Architecture and senior engineers to influence system design and ensure architectural consistency.

Enforce operational maturity and DevOps culture to eliminate production toil.

Collaborate cross-functionally with Product, Compliance, Data Science, and SRE teams to ensure risk and operational excellence.

Required qualifications, capabilities, and skills

5+years of experience as a Machine Learning Engineer and two years in people management roles.

Proven experience leading cloud-native, data-intensive product engineering teams.

Experience building and delivering ML-powered business applications using public cloud providers such as AWS, Azure, or GCP.

Experience in regulated or compliance-driven domains such as fintech, surveillance, or risk.

Strong foundation in Information Retrieval, Natural Language Processing, Classification, and vector similarity search.

Experience integrating models into cloud-scale, distributed systems and microservices architectures.

Excellent verbal and written communication skills, able to explain technical and ML concepts to non-technical stakeholders.

Preferred qualifications, capabilities, and skills

Experience in Data Science and data pipelines.

Exposure to Data Bricks.

Familiarity with vector search, embeddings, RAG patterns, model explainability, and auditability concepts.

Operational experience supporting enterprise-grade ML applications in production.

Lead and coach teams to deliver ML-powered surveillance products with a focus on quality and compliance.

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