
Build, deploy, and maintain production-grade AI/ML solutions for Fortune 500 enterprise clients on Google Cloud Platform. Hands-on role focused on shipping scalable AI systems across GenAI, agentic workflows, traditional ML, and computer vision.
Key Responsibilities:
Generative AI & Agentic Systems
- Design and build GenAI applications (RAG, agentic workflows, multi-agent systems)
- Develop intelligent systems with memory, planning, and reasoning capabilities
- Implement prompt engineering, context optimization, and evaluation frameworks
- Build observable and reliable multi-agent architectures
Traditional ML & Computer Vision
- Develop ML pipelines (forecasting, recommendation, classification, regression)
- Build production-grade computer vision solutions (document AI, image analysis)
- Perform feature engineering, model optimization, and benchmarking
MLOps & Production Engineering
- Own end-to-end ML lifecycle (CI/CD, testing, versioning, deployment)
- Build scalable APIs, microservices, and data pipelines
- Monitor models, detect drift, and implement A/B testing frameworks
Knowledge Solutions
- Architect knowledge graphs and semantic search systems
- Implement hybrid retrieval (vector + keyword search)
Client Collaboration
- Present technical solutions to enterprise clients
- Collaborate with architects, data engineers, and business teams
Required Skills & Experience
- 3–6 years of hands-on ML Engineering experience
- Strong Python and software engineering fundamentals
- Experience shipping production ML systems on cloud (GCP preferred)
- Experience across GenAI, Traditional ML, Computer Vision
- MLOps experience and RAG-based systems
Preferred
- GCP Professional ML Engineer certification
- Knowledge graphs / semantic search experience
- Experience in regulated industries (Healthcare / BFSI)
- Open-source or technical publications

About Quantiphi
About
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to reimagine and realize transformational opportunities at the heart of the business. Since its inception in 2013, Quantiphi has solved the toughest and most complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve accelerated and quantifiable business results.
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