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Tier-1 brand, metro location, and broad generative AI skillset increase applicant competition.
Role requires deep ML engineering and LLM experience, limiting cross-industry transferability.
Explicit 10+ years and 5+ years ML experience plus mandatory tech stack enforce strict filtering.
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Design and deliver scalable generative AI services integrated across multiple applications and thousands of tenants in production.
Drive system efficiencies through automation including capacity planning, configuration management, performance tuning, monitoring, and root cause analysis.
Collaborate across teams including Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to develop AI products focusing on Retrieval-Augmented Generation (RAG), Enterprise Knowledge Graph, and fine-tuned LLM deployments.
10+ years of software engineering experience with at least 5 years in machine learning engineering for AI systems or services.
Experience with distributed, scalable systems and modern data stack technologies such as Spark, Flink, Hadoop, Kafka, Docker.
Proficient programming skills in Java and Python; familiarity with TensorFlow or PyTorch machine learning frameworks.
Experience with LLMs, prompt engineering, vector databases (e.g., Milvus, Pinecone), generative AI frameworks (LangChain, LlamaIndex), and cloud-native architecture on AWS or GCP.
Strong background in developing generative AI systems at scale, especially for NLP and large-scale unstructured data.
Experience applying state-of-the-art machine learning algorithms including neural networks and Bayesian methods, with expertise in LLM fine-tuning and prompt design.
Proven ability to innovate and solve complex, novel AI problems while driving collaboration across multidisciplinary technical and business teams.