Remote Software engineering Jobs · PyTorch

• Define and drive multi-year technical strategy for machine learning across Affirm.
• Lead the design, implementation, and scaling of advanced ML systems.
• Provide technical leadership across the ML organization, mentoring senior engineers.

• Design, implement, and deploy AI-powered features, including model training, fine-tuning, and prompt engineering workflows.
• Translate product requirements into robust, production-ready AI solutions, working with Product Managers, Software Engineers, and Data Scientists.
• Optimize models and infrastructure for scalability, latency, and cost efficiency, partnering with DevOps and MLOps to ensure reliable and maintainable AI pipelines.

• Design, train, and operate ML systems that power the Tebra platform.
• Own the entire lifecycle from data exploration and model development to deployment.
• Push the boundaries of applied ML in healthcare, transforming messy real-world data into reliable automation.

• Implement the company’s AI strategy to set the foundation for AI initiatives.
• Lead the design, development, and rollout of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) based solutions.
• Develop and deploy AI models and solutions into the company’s cloud infrastructure.

• Train and fine-tune text models (LLMs), deploying them on Google Cloud, and building automation around these models.
• Analyse business requirements for the desired output format and the logic the model must implement.
• Develop services and APIs (REST/gRPC) that expose the model to other systems.

• 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.

• 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.

• Design, build, and maintain intelligent, scalable AI systems.
• Develop and maintain MLOps pipelines, integrating CI/CD, model monitoring, and model versioning.
• Work with product and engineering teams to translate business needs into practical, high-impact AI solutions.

• Design, build, and productionize ML models for fine-tuned, Retrieval-Augmented Generation (RAG), and generative AI features.
• Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows.
• Collaborate with product and engineering to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance.

Participate in the design, maintenance, and improvement of Torc's AA frameworks. Work with cloud tools like Terraform, AWS Managed Services, and EKS. Build solutions for AA that have reached the production stage.