Job Summary

We are seeking a Senior Machine Learning Engineer to design, develop, and implement scalable machine learning solutions that bring algorithmic products into production. This role will partner closely with Data Science, Data Engineering, Data Architecture, and Governance teams to build end-to-end ML workflows, data pipelines, and cloud-native architectures. The ideal candidate will have strong expertise in AWS, Python, PySpark, SQL, Docker, and modern machine learning engineering practices, with the ability to architect and implement production-ready ML solutions.

Key Responsibilities
• Design and implement scalable machine learning architectures supporting the full lifecycle of algorithmic products, including data ingestion, model processing, and results activation.
• Partner with Data Scientists to design real-time streaming and batch processing workflows that maximize machine learning model performance and business impact.
• Develop prototype machine learning solutions leveraging AWS cloud services with scalability, performance, and latency considerations.
• Productionize machine learning solutions using Infrastructure as Code (IaC) and cloud-native deployment practices.
• Design and implement data processing pipelines to enhance feature stores with data cleansing, transformation, validation, and feature engineering.
• Optimize and enhance existing machine learning architectures and workflows to improve performance, scalability, and operational efficiency.
• Collaborate with Data Engineering teams to ensure high-quality, reliable, and timely data delivery for machine learning workloads.
• Work closely with Data Architecture, Data Governance, and Security teams to ensure solutions comply with enterprise standards and best practices.
• Design and implement scalable streaming and batch data processing architectures.
• Support CI/CD pipelines, DevOps practices, and automated deployment of machine learning solutions.
• Monitor, troubleshoot, and optimize production machine learning systems.
• Stay current with emerging machine learning engineering technologies, AWS services, and industry best practices.
• Participate in Agile ceremonies and contribute to continuous improvement initiatives.

Required Qualifications
• Master's degree in Computer Science, Software Engineering, or a related technical field.
• 5+ years of experience implementing software solutions for machine learning or algorithmic products in cloud environments.
• Strong expertise with AWS cloud services.
• Strong programming experience with Python.
• Strong SQL development skills.
• Hands-on experience with PySpark.
• Experience with Docker containerization.
• Experience designing and implementing streaming and batch data architectures at scale.
• Experience building and maintaining machine learning pipelines and production ML workflows.
• Experience with Infrastructure as Code (IaC) concepts and cloud-native deployments.
• Strong understanding of DevOps and CI/CD practices.
• Experience working in Agile development environments.
• Strong analytical, problem-solving, and troubleshooting skills.
• Excellent communication, collaboration, and teamwork skills.

Preferred Qualifications
• Experience with Feature Store implementation and management.
• Experience designing real-time machine learning inference pipelines.
• Experience with machine learning model deployment, monitoring, and lifecycle management.
• Familiarity with MLOps tools and best practices.
• Experience working with large-scale enterprise data platforms.
• AWS certifications related to Machine Learning, Data Engineering, or Cloud Architecture.