2 years ago
USA (city not specified)Senior
Base Salary
$175k - $250k/yr
Responsibilities
- Develop distributed training pipelines for complex datasets and models.
- Automate ML experiments, hyperparameter tuning, and model retraining with quantitative researchers.
- Optimize workflows, GPU-accelerated training, and low-latency inference pipelines.
- Extend machine learning frameworks and open-source tools for performance improvements.
- Design scalable infrastructure for high-volume trading data and real-time predictions.
- Evaluate and deploy third-party tools for model development, training, and inference.
Requirements
- At least 3 years of experience in machine learning focused on training or inference systems.
- Production software engineering experience with Python, testing discipline, and ownership of deployed systems.
- Strong understanding of machine learning workloads, model behavior, correctness, and performance beyond high-level APIs.
- Depth in at least one area: distributed training and large-scale systems, GPU performance and low-level optimization, production inference systems, or numerics and correctness at scale.
- Ability to reason about systems performance, scale, reliability, and build-versus-buy decisions.
- Strong collaboration and communication skills when working with researchers and technical teammates.
- Exposure to cloud platforms, orchestration tools, or open-source contributions in machine learning, data science, or distributed systems is a plus.
Benefits
- Full-time permanent employees are eligible for a discretionary bonus.
- Benefits include paid leave and insurance.