Description

You will transform ambiguous business and operational problems into functional machine learning solutions.

Responsibilities

• Design and implement end-to-end ML pipelines, including data gathering, cleaning, preprocessing, training, and evaluation.
• Develop preprocessing strategies for multimodal datasets containing images, multi-spectral sensor outputs, voice, text, and tabular data.
• Deploy, monitor, and maintain models in production, setting up alerting systems to track performance and detect issues.
• Optimize algorithms for real-world environments using quantization, pruning, and TensorRT conversion.
• Collaborate with production, process, controls, and quality teams to integrate ML solutions into existing workflows.

Required Skills

• 5+ years of experience in machine learning engineering.
• Proficiency with PyTorch and TensorFlow.
• Experience with Pandas for data preprocessing and analysis.
• Strong foundation in linear algebra, geometry, probability theory, numerical optimization, and statistics.
• Ability to work with complex data types including CNNs and multimodal inputs.
• Knowledge of model optimization techniques like quantization and pruning.
• Capability to use C++ for performance optimization in embedded or firmware-integrated contexts.
• Experience in computer vision, large language models, recommender systems, or operations research.
• Skill in writing clean, modular, and maintainable code for scalable systems.

Key Skills

Education

Any Gradute