Staff Machine Learning Infrastructure Engineer

Quick Facts

• Role: Staff Machine Learning Infrastructure Engineer

• Team: ML Platform Engineering

• Work authorization: Visa independent only (no visa sponsorship/transfer/C2C)

Description

Architect and lead the technical vision for scalable ML platform infrastructure across data processing, feature management, and model serving. Design and implement next-generation ML platforms for diverse workloads, including robust real-time and batch inference, with strong observability and operational excellence. Mentor platform engineers and drive infrastructure decisions across the ML lifecycle.

Responsibilities

• Architect end-to-end ML infrastructure covering data processing, feature management, and model serving

• Lead implementation of ML platforms supporting diverse ML workloads

• Standardize and automate ML infrastructure for technical excellence

• Build scalable data processing systems and feature platforms for large-scale workloads

• Design ML serving architectures for real-time and batch inference

• Establish best practices for ML observability, monitoring, and operations

• Lead cross-functional technical initiatives and mentor platform engineers

• Define infrastructure decisions that impact the full ML lifecycle

Requirements

• 10+ years of software engineering experience, with 5+ years in ML infrastructure

• Deep expertise in distributed systems and large-scale data processing

• Background in ML platform development and MLOps practices

• Experience building production ML infrastructure for critical business applications

• Proven track record leading complex technical initiatives

• Expert knowledge in Spark/Beam-based large-scale data processing

• Experience with feature store architectures and implementations

• Expert knowledge of ML serving and inference optimization using TorchServe, TensorFlow Serving, and Triton

• Experience with container orchestration and cloud platforms

• Experience designing and optimizing data pipelines

• Experience with ML monitoring and observability

• Visa independent only (no visa sponsorship/transfer/C2C)

Benefits

• Shape the technical direction of ML infrastructure across the organization

• Drive innovation in ML platforms and tools

• Mentor and grow the technical capabilities of the team

• Establish architectural patterns and best practices

• Enable rapid ML development and deployment at scale