Top Remote Python Jobs
The Cloud Devops Engineer will design, develop, and support cloud infrastructure and business applications, automate software installation, monitor performance, ensure security compliance, and implement CI/CD pipelines. Requires expertise in cloud architecture, configuration, and application development across various technologies.
Develop high-performance, low-latency products in Rust, design backend software components, debug production-grade systems, and improve existing codebases while analyzing data accuracy and supporting trading platforms.
The Staff Software Engineer at Moonhub will lead the design, development, and delivery of AI services and products while tackling ambiguous challenges in recruiting through software and AI solutions. This role involves close collaboration with product, design, and recruiting teams to create innovative and scalable systems.
As a Principal Engineer, you will lead backend infrastructure development, mentor junior engineers, design integrations with cloud services and identity solutions, ensure code quality, and drive innovations in identity and access management. You will architect robust solutions and stay updated on industry trends.
The Sr. Backend Engineer will develop and ship high-quality features in a scalable environment, review code for best practices, mentor team members, ensure monitoring of backend services, and participate in Agile ceremonies while solving complex problems.
The Systems Architect Engineer will design and evangelize enterprise solutions across Windows and Linux in an Azure cloud environment, enhance the security and scalability of the SaaS platform, and support the technology teams by implementing innovative solutions. This role requires establishing key relationships with stakeholders and ensuring adherence to security policies while identifying opportunities for improvement in service delivery.
The AWS Integration/Solution Architect will provide leadership in establishing integration standards for the Enterprise Scheduling project. They will convert specifications into programming formats, analyze requirements, perform coding, test systems, coordinate project efforts, and conduct code reviews. A deep understanding of ESB paradigms and proficiency in various coding languages is required.
As a Field Software Engineer, you'll design and deploy cloud infrastructure and applications for clients, work across the Linux stack, and use Python to develop solutions like Kubernetes operators. You'll collaborate with customers, solve problems, and promote engineering culture while learning about various technologies.
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As a Data Platform Engineering Manager, you will lead a team to build scalable data solutions, focusing on data processing from production systems to data lakes and warehouses. You will ensure data quality, mentor engineers, and contribute to platform strategies in a collaborative environment.
Lead the deployment of cloud solutions and secure products for enterprise clients. Spearhead DevOps projects, develop CI/CD pipelines, and implement automation solutions. Mentor team members, facilitate communication across departments, and ensure alignment on project goals. Oversee system documentation and maintain high standards in collaboration and team efficiency.
As a Staff Database Reliability Engineer, you will optimize and manage our critical database systems, including PostgreSQL, Oracle, MySQL, and DynamoDB. Your role will involve collaboration with engineers and developers to enhance performance, availability, and security, utilizing Infrastructure as Code and monitoring tools to ensure optimal system operations.
As a Data Platform Engineering Manager, you will lead a team to develop a robust data platform. Responsibilities include building scalable data systems, ensuring data quality, mentoring team members, and collaborating across departments to enhance decision-making with data.
The role involves leading ML and MLOps initiatives, designing and deploying solutions on AWS while ensuring architecture governance and managing complex model/data pipelines to support Data Scientists. Strong communication and collaboration skills are essential to work with stakeholders and present technical information effectively.
This role involves developing cloud applications utilizing AWS services. Candidates must have extensive experience in Cloud Development, specifically with AWS, Java, and various web technologies. Responsibilities include implementing web applications, utilizing AWS native services, and applying DevOps and Agile methodologies. Independent work with minimal direction is essential.
As a Senior Cloud/Backend Web3 Engineer, you will build and maintain backend systems and cloud infrastructure for a decentralized finance protocol. You'll focus on developing high-performance, scalable solutions for trading platforms and collaborate with the frontend team to ensure integration. Your role includes architecting resilient services and ensuring system reliability through thorough testing and CI/CD practices.
The Staff Software Engineer at Descript will lead initiatives across the engineering organization, build and ship new features for audio and video content tools, and collaborate with product and design teams while ensuring high-quality code and architecture. They will also provide mentorship and make architectural decisions for scalable, efficient systems.
The Senior Software Engineer in Test and Automation will establish robust automation testing frameworks, drive test automation strategies, support continuous integration processes, and ensure high-quality software products while collaborating with cross-functional teams and maintaining test documentation.
The Microsoft Azure Cloud Engineer/Developer will leverage open source technologies for big data processing, ETL, and machine learning. The role involves coding in Java and Python, using Apache tools for data streaming, and optimizing performance in cloud environments. Additional responsibilities include designing and deploying applications and managing cloud services.
As a Senior Software Engineer at Guideline, you will build full stack software solutions for the financial industry, focusing on user interfaces, message queuing, and system architecture. You will work on automating tasks and expanding product offerings while collaborating with a passionate team to enhance the user experience.
As a Senior Machine Learning Engineer at the Wikimedia Foundation, you'll plan, develop, train, document, deploy, and manage production machine learning models. You'll collaborate with internal and external customers to build and maintain scaled models, assess needs, gather training data, and ensure ongoing monitoring and improvement of the models.
The Senior Machine Learning Engineer will develop, train, document, and manage machine learning models, collaborating with product teams and the community to enhance Wikipedia and similar projects. Key responsibilities include assessing customer needs, scoping tools, gathering training data, deploying models, and monitoring their performance over time.
As a Senior Machine Learning Engineer, you will develop, train, document, deploy, and manage production machine learning models. You will collaborate with internal and external customers to build scalable models and support other teams in the Foundation while ensuring the effectiveness of machine learning solutions.
The Senior Machine Learning Engineer will develop, train, document, deploy, and manage production machine learning models for the Wikimedia Foundation. The role involves collaboration with internal teams and the broader community to assess needs and implement scalable machine learning solutions, particularly in NLP tasks while working in a remote environment.
The Senior Machine Learning Engineer will develop, deploy, and manage production machine learning models, collaborating with internal and external customers and teams. Responsibilities include training models, monitoring their performance, and providing insights to improve projects like Wikipedia.
The Senior Machine Learning Engineer will plan, develop, train, document, deploy, and manage machine learning models, collaborating with internal and external teams to meet project needs and monitor model performance over time.
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