scipy jobs in San Diego

Design and develop advanced machine learning models for automotive radar signal processing, including end-to-end ML pipelines from data preprocessing through model training, validation, and performance optimization. Evaluate novel deep learning architectures (CNNs, RNNs, Transformers) for radar data analysis and optimize models for real-time embedded deployment under latency, memory, and power constraints.…See more Bridge research and production by translating state-of-the-art ML techniques into scalable algorithms for radar-based detection, classification, and tracking, with strong requirements in signal processing, statistical analysis, and Python/PyTorch/TensorFlow proficiency.

Sr. SQA Engineer responsible for designing, developing, and executing comprehensive test plans for Pyxa™ Instrument software, including thick-client C# applications, web and cloud applications, and bioinformatics pipelines.…See more The role involves functional, regression, integration, and performance testing of software interfacing with hardware systems, test automation using tools like Selenium and NUnit, defect tracking in Azure DevOps, and collaboration across software, mechanical, electrical, systems, and bioinformatics teams. Requires 6–8 years of SQA experience, ideally with genomics pipelines and cloud applications, proficiency in Windows/Linux/Azure environments, and strong automation and problem-solving skills.

Sr. SQA Engineer will design, develop, and execute comprehensive test plans for thick-client C# applications, web applications, cloud applications, and bioinformatics pipelines.…See more Responsibilities include functional, regression, integration, and performance testing on software interfacing with hardware systems; automating test cases using tools like Selenium and NUnit; identifying and tracking defects in Azure DevOps; and collaborating with software, mechanical, electrical, and bioinformatics engineers. Requires 6–8 years of SQA experience, preferably with genomics pipelines and cloud applications; strong proficiency in Windows, Linux, and Azure; and expertise with test automation frameworks.

The Senior Machine Learning Engineer will design and develop advanced ML models for automotive radar signal processing, including end-to-end pipelines from data preprocessing through model training and optimization. The role requires expertise in deep learning architectures (CNNs, RNNs, Transformers), radar signal analysis, and deploying models for real-time embedded systems with constraints on latency, memory, and power.…See more Responsibilities include evaluating state-of-the-art ML techniques, optimizing models for production, and translating research into scalable algorithms. The position demands a Master's or PhD in a quantitative field, 3+ years of ML research experience, strong proficiency in Python and frameworks like PyTorch or TensorFlow, and foundational knowledge of radar fundamentals.

Design and develop advanced machine learning models for automotive radar signal processing, including end-to-end ML pipelines from data preprocessing through model training and optimization. Evaluate novel deep learning architectures (CNNs, RNNs, Transformers) applied to radar data in time-domain, frequency-domain, and range–Doppler representations.…See more Optimize models for real-time embedded deployment under latency, memory, and power constraints, and translate research outcomes into scalable, production-ready algorithms. Requires a Master's or PhD in a quantitative field, 3+ years of ML research experience, strong radar and signal processing fundamentals, and proficiency in Python, PyTorch/TensorFlow, and cloud platforms.