Software Engineer, ML Infrastructure

What you'll do

• Design and optimize infrastructure systems for machine learning workloads at scale.
• Develop high-performance inference systems to ensure fast and efficient AI model serving.
• Build cloud infrastructure for scalable ML model training, evaluation, and inference.
• Create data management systems for large-scale collection, labeling, processing, and evaluation.
• Implement state-of-the-art vector search algorithms to improve retrieval system precision and scalability.
• Deploy cutting-edge machine learning models into production in collaboration with ML engineers.

What we're looking for

• Bachelor’s degree in a technical field or equivalent experience.
• 6+ years of post-Bachelor’s software development experience, or Master’s plus 5+ years, or PhD plus 2+ years.
• Experience building large-scale production machine learning systems, distributed systems, or big data processing.
• Strong programming skills in Python, Java, Scala, or C++.
• Proficiency with big data processing frameworks such as Spark, Flink, or Ray.
• Proven track record of operating highly-available systems at significant scale.
• Experience working with ML Training platforms or optimizing AI model inference (preferred).
• Familiarity with ML frameworks like TensorFlow, PyTorch, Caffe2, Spark ML, or scikit-learn (preferred).