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Metro location and mid-senior ML hiring increase competition, though GenAI specialization narrows applicants.
High: deep GenAI, NLP, LLM and production ML expertise required, limiting cross-industry transferability.
Explicit 7+ years requirement plus mandatory GenAI, LLMs, and production ML experience increases strictness.
Lead development of scalable generative AI-driven conversational servicebot targeting over a million monthly active users.
Design and implement end-to-end machine learning pipelines including data preprocessing, model building, validation, and deployment for real-time streaming data analysis.
Collaborate with product, business, and ML engineering teams to align GenAI solutions with organizational goals and build high-performance distributed systems using big data frameworks like Hadoop and Spark.
Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, or related field.
Minimum 7 years of relevant work experience in data science or machine learning roles.
Proven experience deploying machine learning projects into production with substantial individual contributions.
Strong programming skills and deep understanding of mathematical foundations of ML including probability, statistics, linear algebra, calculus, and optimization.
Experience applying NLP techniques including prompt engineering, large language models, transformers, and knowledge graphs.
Demonstrated skills in distributed systems, big data technologies, and time series analysis relevant to real-time data processing.
Expertise in at least two core areas: NLP, statistical ML, graph algorithms, constraint optimization, signal processing, deep learning, or distributed systems.