about 4 hours ago
Base Salary
$160k - $240k/yr
Responsibilities
- Transform foundational research ideas into scalable algorithms and prototypes.
- Build evaluation harnesses, datasets, and benchmarks to measure research performance.
- Develop efficient learning methods for relational, tabular, graph, and enterprise datasets.
- Implement fast training and inference pipelines using PyTorch, JAX, or custom kernels.
- Design systems integrating symbolic, relational, and neural components.
- Collaborate with Research Scientists and Systems Engineers to validate and integrate algorithms.
- Run controlled experiments and analyze performance improvements.
Requirements
- Strong background in machine learning, probabilistic modeling, and optimization.
- Experience building algorithms for structured, relational, tabular, or graph data.
- Hands-on experience with PyTorch, JAX, TensorFlow, or similar ML frameworks.
- Strong programming skills in Python; experience with Rust, C++, or CUDA is a plus.
- Proven ability to turn research ideas into performant, reliable code.
- Experience with large-scale ML pipelines or distributed systems is preferred.
Benefits
- Competitive salary, meaningful equity, and substantial bonus for top performers.
- Flexible time off plus comprehensive health coverage for you and your family.
- Support for research, publication, and deep technical exploration.