Senior Ml Platform Engineer (Remote)

SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia.

Position Summary:

We are seeking a highly skilled and experienced Senior ML Platform Engineer to join our platform engineering team. This role is ideal for someone passionate about designing and implementing scalable MLOps processes that support real-time inference and data processing. You will collaborate closely with product engineering, data science, and machine learning teams to enhance our machine learning capabilities and infrastructure.

Responsibilities:

• Develop and maintain scalable and efficient machine learning pipelines capable of processing large volumes of data in real time
• Work independently to deploy, manage, and monitor machine learning models, ensuring high performance and reliability
• Collaborate with product engineering, data science, and ML teams to integrate advanced machine learning features into our products
• Deploy and manage ML models using Kubernetes on AWS, ensuring high availability and low latency for real-time inference
• Implement continuous integration and delivery (CI/CD) processes for machine learning systems, ensuring rapid and safe deployment of features
• Optimize data and feature engineering processes to enhance model performance and reliability
• Monitor and evaluate model performance, making adjustments and improvements as needed
• Ensure compliance with data privacy and security protocols throughout the model lifecycle
• Contribute to the strategic planning and development of ML projects, ensuring alignment with business objectives and technological advancement

Requirements:

• Strong expertise in Python and libraries for machine learning and data processing
• Extensive experience with Kubernetes, including deployments, scaling, and management of containerized applications
• In-depth knowledge of AWS services related to computing, storage, and machine learning
• Hands-on experience with building and deploying generative AI and statistical models
• Solid understanding of feature engineering, data preprocessing, and data integration techniques
• Familiarity with MLOps tools and best practices, including automation, monitoring, and orchestration

Benefits:

• Comprehensive health insurance plan
• Retirement savings plan (401k) with company match
• Remote working environment