Staff SW Engineer, Machine Learning

Jobgether • United States

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Design and deploy machine learning solutions for satellite imagery and geospatial intelligence applications. Collaborate with analytics, infrastructure, and engineering teams to bring research-driven solutions into operational environments. Contribute to mission-critical applications used for monitoring global events and supporting high-stakes decision-making.

Key Highlights

Design and deploy machine learning solutions

Collaborate with analytics and engineering teams

Contribute to mission-critical applications

Key Responsibilities

Design, develop, and deploy machine learning solutions

Conduct applied research in computer vision, time series analysis, predictive modeling, and related domains

Collaborate with infrastructure and ML engineering teams

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Technical Skills Required

Python PyTorch TensorFlow Keras scikit-learn Pandas NumPy GDAL Rasterio Shapely

Benefits & Perks

Competitive compensation package

Comprehensive health coverage

401(k) retirement plan

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Nice to Have

MLOps tools (MLflow, Kubeflow, W&B)

Kubernetes

AWS

Job Description

This role sits at the intersection of advanced machine learning, geospatial intelligence, and production-scale software engineering, focused on transforming satellite and remote sensing data into actionable intelligence. You will design and deploy ML systems that power real-time analytics for complex domains such as computer vision, time series forecasting, and natural language processing. The position requires deep technical expertise in building production-ready models and integrating them into scalable cloud-based systems. You will collaborate closely with analytics, infrastructure, and engineering teams to bring research-driven solutions into operational environments. The work is highly experimental yet production-focused, combining model development, algorithm design, and system integration. You will contribute to mission-critical applications used for monitoring global events and supporting high-stakes decision-making. The environment is fast-moving, technically rigorous, and centered on applied innovation at scale.

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