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Mid-level ML role in metro with common title and moderate employer brand increases competition moderately.
Specialized ML/NLP/LLM skills are transferable but favor ML-focused backgrounds, so medium sensitivity.
Explicit 4+ years plus mandatory LLM/NLP, PySpark, Python, and AWS experience makes filters moderately strict.
Develop and implement high-level machine learning architectures to predict and optimize business outcomes according to client criteria.
Build, test, and productionize ML models using Python, PySpark, SQL, and cloud services (AWS).
Mentor junior ML engineers and liaise with offshore teams and delivery managers for seamless project execution.
4+ years of relevant work experience in machine learning engineering.
Hands-on experience with Python, PySpark, SQL, NLP, LLMs, and productionizing ML models.
Experience with cloud computing services, preferably AWS including Sagemaker.
Have worked on GenAI projects previously.
Experienced in developing end-to-end ML systems and data pipelines in production environments.
Strong expertise with statistical modeling techniques such as Logistic Regression, Cluster Analysis, etc.
Capable of communicating complex ML insights to clients and identifying latent business needs.