Staff SW Engineer, Machine Learning

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff SW Engineer, Machine Learning in the United States.

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.

• Design, develop, and deploy machine learning solutions for satellite imagery and geospatial intelligence applications, leveraging both classical and deep learning techniques.
• Build and optimize production-grade ML models and pipelines in Python, integrating them into large-scale analytics systems.
• Conduct applied research in computer vision, time series analysis, predictive modeling, and related domains to solve domain-specific challenges.
• Develop and refine algorithms, loss functions, and experimental frameworks, including training, evaluation, and performance analysis of models.
• Collaborate with infrastructure and ML engineering teams to ensure scalable, robust, and efficient deployment of analytics systems.
• Translate research concepts from academic literature into production-ready implementations, including experimentation and validation.
• Participate in technical discussions, product strategy alignment, and cross-functional collaboration with stakeholders and leadership.
• Ensure high-quality code delivery, including testing, documentation, and maintainability for long-term system reliability.

Requirements:

• 8+ years of experience in machine learning engineering, data science, or related software engineering roles.
• Bachelor’s degree or higher in Computer Science, Mathematics, Physics, Statistics, or a related quantitative field.
• Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn.
• Proven experience developing and deploying machine learning models in production environments.
• Deep understanding of supervised and unsupervised learning, deep learning architectures, and predictive modeling techniques.
• Experience implementing algorithms from research papers and translating them into working systems.
• Strong background in working with large datasets, including preprocessing, statistical analysis, and visualization using tools like Pandas and NumPy.
• Familiarity with geospatial, remote sensing, or satellite imagery data is highly desirable.
• Strong communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences.
• Nice to have: experience with MLOps tools (MLflow, Kubeflow, W&B), Kubernetes, AWS, or geospatial libraries (GDAL, Rasterio, Shapely).
• Nice to have: exposure to tracking/motion detection, maritime analytics, or asynchronous cloud processing systems.

Benefits:

• Competitive compensation package aligned with experience and location, including base salary and additional benefits.
• Comprehensive health coverage including medical, dental, vision, life, and disability insurance.
• 401(k) retirement plan with employer matching contributions.
• Flexible PTO policy, paid holidays, parental leave, and volunteer time off.
• Employee Stock Purchase Program and additional financial wellness benefits.
• Professional development support, training opportunities, and conference participation.
• Fully remote work flexibility within the United States.
• Access to cutting-edge ML infrastructure, geospatial datasets, and high-impact mission-driven projects.