pandas 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.

Design, develop, test, and maintain scalable backend applications and services using Python for an enterprise technology organization. Build RESTful APIs, optimize application performance, and work with databases and cloud platforms.…See more Collaborate with DevOps teams on CI/CD and production support, participate in code reviews, and mentor junior developers within an Agile environment.

A junior data engineer will contribute to data pipeline development across AWS, Azure, Salesforce, and MuleSoft, learning the full engineering lifecycle with guidance. Core responsibilities include building and maintaining data pipelines, implementing Kimball-based data models, writing Python orchestration and data-quality scripts, and supporting Power BI analytics.…See more The role emphasizes AI-assisted development using Claude Code, Cursor, and GitHub Copilot, with requirements for 0–2 years of experience, 6+ months of Python, intermediate SQL, at least one end-to-end pipeline project, and Power BI/Tableau dashboard experience.

Develop and maintain user-facing applications, dashboards, and workflows within Palantir Foundry, building interactive visualizations and analytics tools that transform complex data into actionable insights. Collaborate with Solutions Architects and data engineers to understand data pipelines and surface data effectively; work directly with Navy stakeholders to gather requirements and iterate on designs.…See more Implement frontend components using Foundry's Workshop, Slate, or similar tools; write and optimize SQL and Python queries to retrieve and transform data. Ensure applications meet usability, performance, and security standards while participating in Agile ceremonies and supporting testing and deployment in production.

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.

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace.…See more Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.

As a Data Developer, you will design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data platforms that integrate enterprise systems and support AI/ML initiatives for the U.S. Navy.…See more You will perform data engineering tasks including cleansing, transformation, and optimization of SQL and Apache Spark workloads on AWS, while also developing predictive models and generative AI solutions using Python-based technologies. You will build interactive dashboards and visualizations in Tableau or Qlik, translating technical findings into actionable insights for stakeholders. An active Secret clearance, U.S. citizenship, and a bachelor's degree in a technical field (or 4+ years of relevant professional experience) are required.

As a client-facing data analyst, you'll work with Department of the Navy clients to understand their data needs, transform complex structured and unstructured data into actionable insights, and advise on how findings impact DoD acquisition programs and IT modernization. You'll use tools like Tableau, Python, R, or SQL for data manipulation; Databricks or Spark for data engineering; and Power Apps/Power Automate for automation.…See more You must hold or be able to obtain a Secret clearance and have 4+ years of DoD client experience.

Senior individual contributor responsible for end-to-end demand forecasting across Intuit's Global Business Solutions Group portfolio. Build and maintain predictive models incorporating time-series analysis, regression, causal inference, and ML techniques to translate business signals into accurate, decision-ready demand forecasts at multiple granularities.…See more Conduct A/B/n experiments to validate modeling choices, quantify forecast risk through scenario analysis, and act as trusted partner between technical teams and business stakeholders (Workforce Management, Capacity Planning, Finance, Marketing, Product) to ensure forecasts drive downstream capacity and expense planning. Continuously advance forecasting methodology, evaluate where AI/ML meaningfully improves accuracy, and support real-time in-season re-forecasting and analytics.