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We are seeking a Machine Learning Engineer to support the design, development, and optimization of machine learning solutions for real‑world applications. This role focuses on model development, data pipeline construction, and performance evaluation within a collaborative engineering environment.
Job Responsibility:
Design, build, train, and evaluate machine learning and deep learning models for production and analytical use cases
Develop and maintain scalable data pipelines for data collection, cleaning, transformation, and ingestion
Conduct experiments and analyze performance metrics such as accuracy, recall, and AUC
Optimize models for performance, speed, reliability, and scalability
Collaborate with cross‑functional teams to support data‑driven solutions
Requirements:
Strong proficiency in Python, including PySpark
Solid understanding of software architecture principles
Hands‑on experience with machine learning frameworks such as Scikit‑learn
Strong foundation in statistics, probability, and algorithm design
Experience with SQL, data modeling, and building data pipelines
Nice to have:
Experience deploying machine learning models using Docker or similar tools (MLOps)
Familiarity with deploying and working with local large language models (LLMs)