Machine Learning Engineer, Applied
Trace · Remote · United States · Remote · NYC ·
COMPENSATION
$185k – $245k
Listed on the employer's job board (Ashby)
- Fully remote
- Python + PyTorch/JAX
- Multimodal data focus
- Early-stage startup
- End-to-end ownership
Join Trace Labs to solve the data scarcity problem in physical AI by building scalable ML systems. You will bridge engineering and research, shipping high-quality models that process real-world interactions from robotics and embodied systems.
The team values practical impact over publications, focusing on rapid iteration and production deployment. You will collaborate with computer vision experts to enhance annotation pipelines and improve model performance across diverse data types.
What you'll do
- Own models end-to-end from data processing to deployment in annotation pipelines
- Build training pipelines for large multimodal datasets including video and sensors
- Partner with engineering and CV teams to productionize and improve models
- Implement simple effective solutions first, then optimize using recent research
- Develop internal tooling to support rapid experimentation across different problems
What you'll need
- BS in Computer Science, Engineering, Math, or equivalent practical experience
- 2+ years of industry experience training deep learning models on real-world data
- Strong proficiency in Python and modern frameworks like PyTorch or JAX
- Solid understanding of ML fundamentals including architectures and optimization
- Comfortable handling messy real-world data such as video and time series
- Demonstrated bias toward shipping working models quickly under uncertainty
- High agency with ability to identify and solve problems independently
Nice to have
- Master’s degree in a relevant technical field
- Experience working across varied data types and problem domains
Stack
- Python
- PyTorch
- JAX