Machine Learning Infrastructure Engineer

NO Visa sponsorship / transfer/ c2c available Machine Learning Infrastructure Engineer Job Type: Full-time - Visa independent only**** Department: ML Platform Engineering About the Role: As a Staff Machine Learning Infrastructure Engineer, you will architect and lead the technical vision for our ML platform initiatives, focusing on building scalable infrastructure that powers our ML capabilities. You will design and drive the evolution of our ML platforms, data systems, and serving infrastructure that enable teams to efficiently develop, deploy, and operate ML models at scale. Key Responsibilities Architect end-to-end ML infrastructure spanning data processing, feature management, and model servingDesign and lead implementation of next-generation ML platforms that support diverse ML workloadsDrive technical excellence in ML infrastructure through standardization and automationBuild scalable data processing systems and feature platforms that handle massive-scale ML workloadsDesign robust ML serving architectures supporting both real-time and batch inferenceEstablish best practices for ML observability, monitoring, and operational excellenceLead cross-functional technical initiatives and mentor platform engineersDrive infrastructure decisions that impact the entire ML lifecycle Technical Leadership Define technical strategy and roadmap for ML infrastructureDrive architectural decisions for complex ML systemsLead design reviews and provide technical mentorshipCollaborate with data science teams to understand and address infrastructure needsEstablish standards for reliability, scalability, and performanceBuild frameworks and platforms that accelerate ML development Required Qualifications 10+ years of software engineering experience, with 5+ years focusing on ML infrastructureDeep expertise in distributed systems and data processing at scaleStrong background in ML platform development and MLOps practicesExperience building production ML infrastructure supporting critical business applicationsProven track record of leading complex technical initiativesExpert-level knowledge in:Large-scale data processing systems (Spark, Beam)Feature store architectures and implementationsML serving platforms and inference optimization (TorchServe, Tensorflow Serving and Triton)Container orchestration and cloud platformsData pipeline design and optimizationML system monitoring and observability Technical Expertise Data Infrastructure:Feature stores and feature computation systemsData quality and validation frameworksDataset versioning and lineage trackingEfficient data storage and access patternsServing Infrastructure:Model deployment and serving platformsInference optimization and scalingLoad balancing and traffic managementModel versioning and lifecycle managementPlatform Development:MLOps tooling and automationExperimentation platformsMonitoring and observability systemsResource management and optimization Preferred Qualifications Experience with GPU infrastructure and optimizationBackground in high-performance computingContributions to open-source ML infrastructure projectsExperience with ML-specific security and compliance requirementsMaster's degree in Computer Science or related field Impact Shape the technical direction of ML infrastructure across the organizationDrive innovation in ML platforms and toolsMentor and grow the technical capabilities of the teamEstablish architectural patterns and best practicesEnable rapid ML development and deployment at scale