Remote Software engineering Jobs · Python

• Lead the design, development, and deployment of AI/ML models.
• Build and maintain production-grade ML pipelines and model monitoring.
• Mentor and develop junior AI engineers, laying the foundation for AI best practices.

• Building features and maintaining back-end services using Go microservices.
• Deploying Weave software solutions into Google Cloud Platform.
• Designing and maintaining services that can scale and grow independently.

• Develop Machine Learning models and pipelines.
• Interact with databases and data infrastructure.
• Conduct in-depth data analytics and build statistical data inference models of biological processes.

The AI Engineer develops and deploys agentic AI solutions for clients. Implements components for document processing, workflow automation, data retrieval, and structured output generation. Contributes to monitoring, logging, metrics, and guardrail configurations for agentic systems.

• Contribute to all phases of product development, from ideation and prototyping to implementation and iteration.
• Build and evolve both frontend product experiences and backend services that power them.
• Design reliable and scalable backend services to support new features in production.

• Design and deliver core functionality for a large-scale web application.
• Lead architectural planning and create technical proposals.
• Develop and maintain complex UI components, including CKEditor integrations and DocX formatting workflows.

• Build infrastructure that enables quality monitoring across Design Generation.
• Guide Design Generation teams on how to evaluate their systems effectively.
• Build platforms that make evaluation accessible and automated.

Managing and mentoring software developers. Leading technical projects. Architecting technical solutions.

• Design and deploy complex ML systems to improve ad performance.
• Collaborate with global teams to refine algorithms for ad targeting and relevance.
• Apply cutting-edge ML approaches to enhance ad performance and optimize revenue.

• Build scalable backend services and APIs.
• Create responsive dashboards and tools to manage automation systems.
• Implement automation workflows to power real-time operations.