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