Remote Software engineering Jobs • Python

Build AI systems that make finance simpler, smarter, and more inclusive. As a Machine Learning Engineer, you’ll develop and deploy models that power key features - from personalization and risk scoring to intelligent automation and fraud detection. Your work will have a direct and visible impact on millions of users across the region.

As a Senior Forward Deployed Engineer at Invisible, you'll lead high-impact, AI-powered solutions that reshape how our clients operate their most critical workflows. You won’t just build and deploy — you’ll drive the strategy, architecture, and execution of end-to-end systems, working directly with client stakeholders and our internal delivery teams. This is a hybrid role: equal parts AI architect, hands-on engineer, and technical advisor.

Join the Payment Processing crew at Alan as a Software Engineer! You'll be building a unified payment platform that powers Alan's products across multiple markets, providing robust, scalable payment solutions while maintaining the highest standards of security and compliance. This role involves working with third-party API integration, monitoring complex systems, and designing maintainable, decoupled systems.

Design, develop, and optimize graph-based ML models for large-scale recommendation systems. You will work on embedding generation, distributed training, and scalable serving architectures, playing a key role in improving Reddit’s AI-powered personalization. This role offers the opportunity to contribute to cutting-edge ML research and apply it at scale in a high-impact production environment.

The mission of the Platform Product Group engineers is to build a trusted, scalable and compliant platform to operate with speed, efficiency and quality. As a Staff Machine Learning Platform Engineer at Coinbase, you will play a pivotal role in building an open financial system. You will build the foundational components for training and serving ML models at Coinbase. You will get the opportunity to apply your software engineering skills across all aspects of building ML at scale.

As a Full-stack Engineer, you will build scalable web platforms. You will provide input on app architecture, create and review pull requests daily and engage with internal teams and directly with clients in an agile environment. You will work in teams with a product manager, designers, and other engineers to scope design and implement features.

Develop and maintain backend services using Python (e.g., Flask, Django, FastAPI). Design and implement RESTful APIs for internal and external use. Work with databases (SQL and NoSQL) such as PostgreSQL, MySQL, or MongoDB. Write unit and integration tests to ensure software reliability and maintainability. Participate in code reviews, refactoring, and improving legacy codebases. Monitor and optimize performance of Python applications.

We are looking for engineers with 10+ years of experience to help us scale our Engineering community from different perspectives (product, tech, and internal organization-wise). You’ll be able to tackle high-impact & high-risk projects involving many engineers and design efficient systems and engineering practices to align with and facilitate interactions between multiple teams/products. You’ll have the opportunity to mentor other engineers & lead crews.

Implement robust back-end services and APIs, writing clean, maintainable, and efficient code. Optimize applications for peak performance and scalability. Validate the technical feasibility of system designs and contribute actively to all development lifecycle phases. Focus on operational excellence with strong test coverage, monitoring, intuitive metrics, and alerting.

Build and deploy ML models and tools that support personalization, automation, and insight generation, helping develop scalable ML infrastructure and pipelines, and integrating ML outputs into products and user-facing features. Work with product and data teams to define machine learning goals and strategies, handle data preprocessing, feature engineering, and model training/evaluation.