We’re seeking a Machine Learning Engineer with strong data engineering expertise to build scalable real-time data pipelines and develop advanced ML models. This role involves collaborating with cross-functional teams to deliver innovative solutions.Key Responsibilities:– Data Engineering: Build and maintain real-time data pipelines and ETL workflows. Ensure data quality and integrity.
– Machine Learning: Design, train, and optimize ML models for fraud prevention and personalization.
– MLOps: Deploy, monitor, and maintain ML models in production using tools like Docker, Kubernetes, and cloud platforms (AWS/GCP).
– Data Analysis: Preprocess data, identify trends, and derive insights using clustering, classification, and anomaly detection techniques.
– Collaboration: Work with product managers, engineers, and data scientists to align technical solutions with business goals.What We’re Looking For:
– Experience: 2+ years in ML, data engineering, or related fields, with a focus on fraud detection or personalization.Technical Skills:
– Proficiency in Python, SQL, and big data tools (e.g., Kafka, Spark).
– Strong knowledge of ML frameworks (TensorFlow, PyTorch).
– Experience with MLOps and cloud technologies (AWS/GCP).
– Analytical Skills: Strong understanding of statistical methods and data visualization tools (e.g., Pandas, Matplotlib).
– Mindset: Adaptable, innovative, and comfortable in a fast-paced environment.
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