This is a fully remote position, open to applicants in United States.

📋 Description

• Take full responsibility for models from inception to deployment: encompassing data management, training, evaluation, and integration into the annotation pipeline.

• Develop training pipelines for extensive, multimodal datasets, which include video, sensor data, and language.

• Collaborate with the Head of Engineering and the computer vision team to implement models in production and continuously enhance them.

• Begin with the simplest effective solution, subsequently refining it by leveraging recent academic research when beneficial.

• Swiftly transition between various challenges and construct the necessary tools.

• Engage in both ML engineering and research to tackle complex issues and deliver solutions into production.

⛳️ Requirements

• A Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Aerospace, or a related discipline, or equivalent practical experience.

• Over 2 years of hands-on experience in the industry training deep learning models with real-world datasets.

• Strong expertise in Python and familiarity with a contemporary deep learning framework such as PyTorch or JAX.

• A solid understanding of ML fundamentals, including architectures, optimization strategies, loss function design, and evaluation techniques.

• Experience working with messy, real-world data such as video, time series, or sensor streams.

• A strong inclination towards delivering results.

• High level of initiative and autonomy.

• Versatility across various types of data and problem domains.

• A Master's degree is a plus, but not a requirement.