Senior Machine Learning Engineer, AI Infra

What you'll do

• Lead the architecture and end-to-end delivery of scalable systems for deploying, monitoring, and managing ML models in production.
• Own the technical direction for core platform components including model serving, feature stores, and observability infrastructure.
• Partner with data engineers and ML practitioners to streamline workflows and accelerate experimentation across the organization.
• Scale the feature store to support low-latency retrieval for both real-time and batch use cases.
• Implement robust observability standards for model performance, data pipelines, and feature freshness.
• Manage and optimize cloud compute resources on AWS to ensure cost-effective, high-throughput training and inference.
• Contribute to technical strategy and roadmap discussions while mentoring junior engineers through design reviews.

What we're looking for

• 6+ years of software engineering experience with depth in ML infrastructure, data engineering, or model operations.
• Demonstrated ability to own and deliver complex platform systems from architecture to production.
• Deep expertise in model serving, distributed systems, and production ML workflows at scale.
• Proficiency in Python, C++, or similar languages and hands-on experience with TensorFlow or PyTorch.
• Knowledge of modern ML infrastructure tooling such as Ray, Kubeflow, SageMaker, TensorFlow Serving, or Triton.
• Experience with large-scale search systems including embedding models, vector databases, and distributed retrieval engines.
• Experience influencing technical direction across teams and mentoring engineers at various levels.
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field (advanced degree preferred).