model-validation jobs in San Diego

Join XiFin's Advanced Data Analytics team as an Associate Machine Learning Engineer to design, develop, and deploy machine learning models with a focus on LLMs, Generative AI, and Agentic AI in healthcare and revenue cycle domains. You will contribute to MLOps pipelines, perform data preparation and prompt engineering, collaborate with cross-functional teams, and validate models for production use.…See more The role requires a Bachelor's degree in Computer Science, Data Science, or related field, with proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and foundational knowledge of GenAI architectures, vector databases, and LLM orchestration frameworks.

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.

Qualcomm seeks a Software Test Engineer to validate on-device AI solutions across mobile, PC, and automotive platforms, with emphasis on generative AI models (LLMs, LVMs, LoRA, agentic workflows) and system-level performance across SoC components (CPU, GPU, DSP, NPU). The role involves designing end-to-end validation workflows, developing test automation frameworks in Python/Java/Shell, analyzing model outputs for accuracy and robustness, and conducting stability and performance testing.…See more Candidates should have 1–3+ years of software testing or AI validation experience (or be fresh graduates with strong AI/ML fundamentals), proficiency in Python, Java, and Linux, and solid understanding of AI inference, RAG systems, and multi-step reasoning pipelines.

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.

Senior Engineer, Machine Learning at Element Biosciences will design, develop, and optimize deep learning models (CNNs, Vision Transformers, U-Net) for biological image analysis and deploy them to production on AWS or imaging instruments. Responsibilities include building end-to-end ML pipelines from data ingestion through inference, applying advanced image processing and computer vision techniques to multimodal biological images, and analyzing single-cell and multiomic data.…See more The role requires 5–7 years of experience with a Master's degree (or 0–3 years with a PhD) and hands-on proficiency in PyTorch, Python, and cloud deployment, with strong preference for experience in biomedical image modalities.