Top Remote Senior Level Python Jobs in Washington DC,

As a DevOps Engineer at Lucidworks, you will be responsible for developing automation tools and collaborating with engineering teams to ensure high-quality product delivery. Your focus will be on maintaining production infrastructure for cloud-based services, achieving high uptime, and improving customer onboarding processes while managing large-scale distributed systems.

The Principal Full-stack Software Engineer will work in the Special Projects team at Shield AI, focusing on architecting and building AI interfaces for seamless human-AI interaction. The role involves integrating various Hivemind products and contributing to the development of foundational software technologies.

As a Full Stack Engineer, you will develop and maintain both backend services and frontend components for a data labeling platform. Your responsibilities include designing APIs, creating responsive user interfaces, collaborating with teams on product goals, and mentoring junior engineers.

As a Backend Software Engineer at Parse.ly, you will be responsible for writing high-quality Python code, analyzing large datasets, and ensuring the reliability and performance of backend services. You will collaborate on new product ideas, master cloud technologies, and participate in on-call rotations.

Cube Dev is seeking a Principal Software Engineer for its Cube Core team to focus on building and maintaining analytics data access technology. Responsibilities include SQL generation, optimizing data storage and retrieval systems for performance, and developing analytics operations management features, all while supporting an open-source community and collaborative development environment.

As a Senior or Team Lead NLP Engineer, you will develop and enhance ML services, manage NLP projects, build training pipelines, and lead team workflows while ensuring the confidentiality and quality of conversational AI products.

As a Senior Search Engineer, you will optimize and scale search infrastructure using Elasticsearch, focusing on search performance, relevance, and technical implementations. Responsibilities include architecting clusters, tuning performance, developing ranking algorithms, and implementing advanced search features and monitoring tools.