Top Tech Jobs & Startup Jobs in Los Angeles, CA

Lead the development of statistical and machine learning models for time-series and geospatial data. Build analytic solutions, datasets, ETL workflows, forecasting and anomaly-detection models, simulations, visualizations, and reports. Evaluate algorithm performance, optimize classifiers, document processes, and collaborate with engineers, analysts, mission partners, and stakeholders to deliver reliable mission-focused software and data capabilities.

Lead and contribute to the design, integration, deployment, and sustainment of mission-focused systems. Translate stakeholder needs into technical requirements, architectures, interface definitions, deployment patterns, and operational processes. Partner with software engineers and data scientists to integrate applications, data pipelines, infrastructure, and external systems. Support testing, verification, troubleshooting, operational readiness, documentation, and reliability improvements for secure, scalable, data-intensive systems.

Develops statistical and machine learning models for kinematic behavior detection using live, historical, time-series, and geospatial data. Responsibilities include data integration, ETL, feature engineering, forecasting, anomaly detection, algorithm evaluation, simulation, visualization, reporting, documentation, and stakeholder collaboration. The role also contributes to mission-focused software applications, APIs, data workflows, code reviews, troubleshooting, and agile development in a remote-first environment.

Lead development of statistical and machine learning models for time-series, geospatial, kinematic, and radar data. Build analytic solutions, training datasets, ETL workflows, forecasting and anomaly-detection models, simulations, visualizations, and performance metrics. Integrate multi-source sensor data, enhance algorithms, document processes, and collaborate with engineers, analysts, mission partners, and stakeholders in an agile environment.

Design, develop, and productionize multimodal AI systems (VLMs, reasoning models, LLMs) for geospatial data. Build end-to-end ML pipelines, experimentation frameworks, synthetic datasets, and scalable inference on cloud infrastructure while collaborating with research, engineering, and product teams.

Design, develop, and productionize multimodal AI systems (VLMs, LLMs, reasoning models) and end-to-end ML pipelines for geospatial data. Build training/experiment frameworks, synthetic datasets, scalable inference, monitoring, and collaborate with research, engineering, and product teams to deliver Earth intelligence solutions.