Machine Learning Systems Engineer: Distributed Training

**Overview:**
We're seeking a talented Machine Learning Systems Engineer to join our team and strengthen the performance and scalability of our distributed training infrastructure. As a key member of our team, you'll work closely with researchers to develop and execute large-scale training runs, and contribute to building tools that make distributed training more efficient and accessible. **Responsibilities:**
• Collaborate with researchers to enable them to develop systems-efficient models and architectures
• Apply the latest techniques to our internal training runs to achieve impressive hardware efficiency for our training runs
• Create tooling to help researchers distribute their training jobs more effectively
• Profile and optimize our training runs
• *Qualifications:**
• Experience with large-scale ML training pipelines and distributed training frameworks
• Strong software engineering skills in Python
• Passion for diving deep into systems implementations and understanding fundamentals to improve their performance and maintainability
• Experience improving resource efficiency across distributed computing environments by leveraging profiling, benchmarking, and implementing system-level optimizations
• *Benefits:**
As a Machine Learning Systems Engineer at Susquehanna, you'll be part of a global quantitative trading firm that combines deep research, cutting-edge technology, and a collaborative culture. You'll play a critical role in shaping the future of AI at Susquehanna, enabling research at scale, accelerating experimentation, and helping unlock new opportunities across the firm