Machine Learning Platform Engineer

About Our Client:The organization operates in the North American sports and daily fantasy sports (DFS) industry, providing an engaging platform covering multiple professional sports leagues and esports titles. With more than 550 employees, the company fosters an inclusive environment while delivering technology that supports diverse sports fandom and real-time sports experiences.About the Opportunity:The Machine Learning Platform Engineer develops and scales the machine learning infrastructure supporting the organization’s core capabilities. This role enables reliable, low-latency machine learning models across sports betting and daily fantasy products, helping improve real-time decision-making, operational efficiency, and key business outcomes.Responsibilities:• Design and build end-to-end machine learning infrastructure to transition experimental models into production.• Develop automated, low-latency services for real-time model inference.• Lead the creation and optimization of a centralized feature store supporting complex model training and production workloads.• Collaborate with infrastructure teams to build and operate machine learning platform components with a strong focus on developer experience.• Establish and implement best practices for model deployment, monitoring, CI/CD, automated retraining, and system observability.• Monitor and address data drift, model degradation, and other production performance issues.• Support reliable, scalable machine learning systems in high-traffic environments.Requirements:• 3+ years of platform engineering experience, including deploying and maintaining scalable machine learning platforms in high-traffic environments.• At least 1 year of experience managing machine learning systems end-to-end in production, including on-call and incident response.• Proficiency with real-time data and streaming architectures such as Kafka, Flink, or Pub/Sub.• Expertise with MLOps tools and platforms such as SageMaker, Vertex AI, and vector databases.• Experience managing caching and search technologies such as Redis or Elasticsearch.• Strong experience with containerization technologies, including Docker and Kubernetes.• Strong programming skills in Python.• Proficiency in Go, C++, or Rust is advantageous.Pay Range and Compensation Package:• Typical salary range of $155,000–$185,000 annually.• Actual compensation may vary based on location, skills, experience, education, and other relevant factors.Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.Note:TalentHop is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.