Senior ML Engineer

Responsibilities

• Build, train, and deploy machine learning models efficiently with the managed infrastructure and automation capabilities of AWS SageMaker;
• Utilize Amazon Redshift and S3 for data storage, processing, and analysis;
• Utilize Apache Spark and Airflow for large-scale data processing and pipeline orchestration;
• Manage and optimize machine learning workloads on Amazon EMR;
• Proficiency in Python and its data science libraries (e.g., NumPy, Pandas, Scikit-learn) for data manipulation, modeling, and analysis;
• Collaborate with data engineers to ensure seamless integration of ML models into production environments;
• Implement best practices for model versioning, monitoring, and continuous deployment.

Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field;
• Proven experience designing, building, and deploying production-grade machine learning models;
• Extensive experience with AWS services like SageMaker, Redshift, S3, EMR, and other relevant AWS data and ML services;
• Strong proficiency in Python and its data science (e.g., NumPy, Pandas, Scikit-learn etc.);
• Expertise in Airflow and Spark;
• Excellent problem-solving and analytical skills;
• Strong communication and collaboration skills.