Staff SW Engineer, Machine Learning

BlackSky is a real-time intelligence company that operates the world's most advanced space-based intelligence platform. They are seeking a Staff SW Engineer with a focus on integrating machine learning into automated systems, requiring expertise in various challenging ML tasks in computer vision, time series, and natural language domains.

Responsibilities:

• Design and implement solutions for internal and external customers that exploit traditional machine learning and novel deep learning for next-generation satellite imagery analytics
• Plan and conduct research projects related to computer vision, time series analysis, content curation, probabilistic modeling, machine learning, predictive analytics, and geometric modeling
• Develop algorithms, models, and analytical tools for solving domain specific business problems
• Implement production quality analytics and models into the SpectraAI codebase (Python)
• Collaborate with management and technical team on product strategy
• Collaborate with infrastructure developers and machine learning quality engineers to build robust analytics for production use cases
• Independently design and conduct experiments, tests hypothesis, implement model and loss function code, train models, and interpret experiment results following a machine learning process based on high level project objectives
• Other job-related duties as assigned

Requirements:

• At least eight years of hands-on experience as a machine learning engineer or data scientist
• Bachelor's Degree or higher in one of the following fields: computer science, mathematics, physics, statistics, or another computational field with a strong background of using machine learning/data mining for predictive modeling or time series analysis
• Extensive experience developing machine learning based software solutions. In particular, developing models in Python 3, PyTorch, Tensorflow, Keras, or scikit-learn
• Working knowledge of a wide range of machine learning concepts including supervised and unsupervised deep learning methods for both classification and regression
• Experience performing research in both groups and as a solo effort with a history of implementing algorithms directly from research papers
• Experience conducting literature review and applying concepts to programs or products
• Strong ability to communicate concepts and analytical results with customers, management, and the technical team, highlighting actionable insights
• Hands-on experience working with large data sets including data cleansing/transformation, statistical analyses, and visualization (using Python libraries such as Pandas, NumPy, etc.)
• PhD./Master's degree in the previously mentioned fields
• Experience working with remote sensing data, ideally satellite imagery
• Experience with cloud-based MLOps tools such as ClearML, Weights & Biases, Kubeflow, or MLFlow
• Experience working with Kubernetes-based infrastructure
• Experience with tracking and motion detection algorithms
• Experience with maritime data for analysis and modeling
• Experience working with geospatial data and geospatial Python libraries (GDAL, shapely, rasterio, etc.)
• Experience developing asynchronous processing algorithms and Cloud-based solutions (especially AWS services like EC2 & S3)