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Tier-1 brand, metro location, mid-level generalist ML role with broad LLM/MLOps requirements.
Core ML, LLM, MLOps, and cloud skills are highly transferable across industries.
Explicit 6+ years requirement plus mandated ML, LLM, MLOps, cloud, and Kubernetes skills.
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Own the end-to-end machine learning lifecycle: design, develop, deploy, monitor, and improve AI/ML and GenAI cloud solutions using MLOps.
Build and maintain scalable AI-driven cloud applications featuring LLMs, RAG, and agent workflows, ensuring secure, reliable deployments.
Collaborate with cross-functional teams to architect and deliver measurable AI/ML solutions that enhance digital customer experiences.
Bachelor's degree in Computer Science, Engineering, Information Systems, or related quantitative discipline; Master's degree desirable.
6+ years of professional experience with hands-on expertise in AI/ML technologies and cloud-native development.
Proficient in Python, SQL, machine learning frameworks (Scikit-learn, PyTorch, TensorFlow), LLMs and related tools (LangChain, LangGraph, LlamaIndex).
Experience with data pipelines, AI evaluation tools (MLflow, Langfuse, Arize Phoenix), containerization (Docker, Kubernetes), CI/CD, and cloud platforms (AWS, Azure, or GCP).
Technically strong AI/ML engineer with advanced expertise in designing, deploying, and maintaining mission-critical, production-grade cloud AI systems using modern MLOps practices.
Experienced in applying GenAI technologies and building AI services/APIs integrated with scalable cloud architectures.
Capable of providing technical leadership, mentoring peers, and influencing cross-team best practices for AI/ML development and operations.