Sr AI Engineer
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Key skills for this role
Role Overview
Build, deploy, and maintain AI/ML applications supporting automation, insights, and action across core business workflows.
Work with data scientists, engineers, product partners, platform teams, security teams, and business stakeholders.
Deliver production-grade ML/AI applications and serving systems that create measurable business value.
Key Skills for This Role
Full Job Posting
Role overview
Build, deploy, and maintain AI/ML applications supporting automation, insights, and action across core business workflows.
Work with data scientists, engineers, product partners, platform teams, security teams, and business stakeholders.
Deliver production-grade ML/AI applications and serving systems that create measurable business value.
Core responsibilities
- Write maintainable, well-tested code and support model and framework integration.
- Build APIs, services, data and application workflows, batch or online inference, and retrieval or vector-based systems.
- Contribute to deployment, monitoring, documentation, production support, security, reliability, and operational readiness.
- Evaluate technical options, identify implementation risks, resolve engineering roadblocks, and improve reusable AI engineering patterns.
- Stay current with AI, machine learning, agentic systems, and modern software engineering practices.
About you
- Four-year degree in a quantitative discipline or equivalent experience.
- At least 5 years of hands-on software engineering experience, including production data science or machine learning systems.
- Experience building and scaling production ML/AI applications, intelligent automation, and agentic systems.
- Strong Python proficiency and experience productionizing models, building APIs and services, and developing data or model pipelines.
- Experience with MLOps, model evaluation, observability, CI/CD, containers, cloud deployment, reliability, and performance optimization.
- Strong understanding of system design, AI application architecture, experimentation, scalability, latency, and production deployment.
- Experience with maintainable, well-tested production systems, version control, code reviews, documentation, monitoring, and production support.
- Ability to translate requirements into pragmatic solutions, work independently, collaborate effectively, and exercise strong engineering judgment.
- Experience with Google Cloud Platform is preferred; exposure to LLM evaluation, retrieval quality, and agent observability is a plus.
About Target
Target is a large global retailer with a data science organization focused on predictive algorithms, automation, and decision optimization.
Target in India operates as an integrated part of Target's global team and supports global strategy and operations from Bengaluru.
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