Optimize LLM performance and implement evaluation frameworks; build clustering models for customer and product segmentation; design and maintain data pipelines using SQL and Python DAGs.
We are seeking a highly skilled Machine Learning Engineer with 4+ years of experience to bridge the gap between Generative AI and actionable business intelligence. You will be responsible for optimizing Large Language Model (LLM) performance and building sophisticated clustering models to drive customer and product segmentation.
Key Responsibilities:
- LLM Optimization: Maximize the accuracy and minimize the latency of LLM-powered applications.
- Performance Evaluation: Implement robust LLM evaluation frameworks to ensure high-quality outputs.
- Advanced Analytics: Segment customers and products into meaningful clusters by incorporating complex business logic into ML models.
- Data Orchestration: Build and maintain efficient data pipelines using SQL and Python DAGs.
Technical Requirements:
Mandatory Skills:
- LLM: Proven experience in LLM Evaluation; familiarity with LLM APIs is a strong plus.
- Machine Learning: Expertise in Clustering techniques.
- Data Processing: Strong proficiency in SQL and developing Python-based DAGs (e.g., Airflow).
Preferred (Bonus) Skills:
- Advanced LLM: Experience in self-hosting and fine-tuning LLMs.
- Extended ML: Proficiency in Time Series Forecasting, Dimension Reduction, and Market Basket Analysis.
- Big Data Tools: Hands-on experience with Spark and Alteryx.
Top Skills
Airflow
Alteryx
Large Language Models (Llms)
Llm Apis
Python
Spark
SQL
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