Machine Learning Engineer
Core
Architecting and developing the next generation of Tower's machine learning research platform, enabling large-scale experimentation, model training, and simulation for quantitative researchers.
Role type
Senior IC machine learning platform engineer
Builds
Scalable, reliable, and reproducible ML research infrastructure supporting on-premises HPC and multi-cloud environments
Domain
Quantitative finance / High-performance computing / Distributed systems
Deliverable
production ML models | infrastructure
Required skills
Python, distributed systems design, Linux HPC operations, GPU workload optimization, ML frameworks (PyTorch, TensorFlow, JAX), data pipeline optimization, system debugging
Preferred skills
Internal ML platform building, experiment tracking systems, workflow orchestration, containerization (Docker, Kubernetes), quantitative finance domain knowledge
Technologies
PyTorch, TensorFlow, JAX, Docker, Kubernetes, Linux, HPC clusters, multi-cloud environments
Responsibilities
Architecting scalable ML research platforms, building infrastructure for large-scale model training and simulation, partnering with researchers to translate workflows into platform capabilities, designing distributed training pipelines, improving experiment management and data lineage, developing tools for feature engineering and backtesting, optimizing compute efficiency and resource scheduling, enhancing platform observability, supporting rapid iteration, contributing to long-term architectural decisions
Seniority
Senior, hands-on IC
