Develop, train, and fine-tune machine learning models for multimodal sensor data, focusing on supervised and self-supervised learning approaches
Job Summary
Develop, train, and fine-tune machine learning models for multimodal sensor data, focusing on supervised and self-supervised learning approaches.
Build embedding-based search tools and active learning workflows to identify critical driving scenarios and accelerate the model improvement lifecycle.
Follow software engineering standards including version control, CI/CD, and unit testing, while collaborating with senior engineers to translate prototypes into scalable solutions.
Matching Summary
Develop, train, and fine-tune machine learning models for multimodal sensor data, focusing on supervised and self-supervised learning approaches.
Salary
$144,000 - $192,000 USD
Skills & Requirements
Must-have
PyTorch or TensorFlow/JAX
Python programming
SQL and data libraries
ML lifecycle
Version control and unit testing
Nice-to-have
Agentic systems and LLMs
Autonomous driving background
Multimodal learning and sensor fusion
Active learning loops
ML-based data mining
Key Requirements
BS or MS in Computer Science, Machine Learning, or related field
Hands-on PyTorch experience
Proficiency in Python
Working knowledge of version control, unit testing
Experience with large datasets, SQL, Pandas, NumPy