Senior Machine Learning Engineer

Who you are

• 6+ years of software engineering experience, with meaningful depth in ML infrastructure, data engineering, or model operations
• Demonstrated ability to own and deliver complex platform systems end-to-end, from architecture to production
• Deep expertise in model serving, distributed systems, and production ML workflows at scale
• Strong proficiency in Python, C++, or similar languages, and hands-on experience with ML frameworks such as TensorFlow or PyTorch
• Solid knowledge of modern ML infrastructure tooling (e.g., Ray, Kubeflow, SageMaker, TensorFlow Serving, Triton)
• Hands-on experience with large-scale search systems, including embedding models, vector databases, and distributed retrieval engines using platforms such as Qdrant, ChromaDB, or Elasticsearch with dense vector search capabilities
• Experience influencing technical direction across teams and mentoring engineers at varying levels
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field; advanced degree a plus

What the job involves

• 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 key platform areas — including model serving, the feature store, and ML observability infrastructure — from design through long-term reliability
• Drive cross-functional partnerships with ML practitioners, data engineers, and applied AI teams to streamline workflows, reduce friction, and accelerate experimentation
• Evolve and scale our feature store to support efficient, low-latency feature retrieval across real-time and batch use cases
• Define and implement robust observability standards for model performance, data pipelines, and feature freshness across the ML platform
• Manage and optimize cloud compute resources (CPU/GPU) on AWS to support cost-effective, high-throughput training and inference at scale
• Contribute to technical strategy and roadmap discussions, and help mentor engineers on the team through design reviews and hands-on guidance