Machine Learning Engineer

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: Python, SQL, and big data tools (e.g., Kafka, Spark).ML Frameworks: Strong knowledge of ML frameworks (TensorFlow, PyTorch).MLOps: 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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