Senior Software Engineer, GenAI Platform

About the Role

The Machine Learning Platform team is a high-impact team that directly influences other critical teams, such as Growth, Ads, Feeds, and Core Machine Learning. Your work will have a significant impact on Reddit's ability to provide personalized and engaging experiences for its users. You will be working closely with a talented team of engineers, researchers, and product managers to push the boundaries of what is possible with AI and machine learning.

Reddit is committed to fostering a culture of innovation, collaboration, and mutual respect. As a Senior Software Engineer, you will be expected to embody these values and contribute to the company's mission to make the world a better place through community and technology.

What You Will Do

• Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.
• Design and develop ML and generative AI systems in cloud-based production environments at scale.
• Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
• Implement and operationalize agentic AI workflows with tool use using frameworks such as LangChain and LangGraph.
• Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
• Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.
• Collaborate with cross-functional teams to integrate the GenAI Platform with other Reddit systems and services.
• Participate in code reviews and contribute to the improvement of the overall code quality and architecture.
• Stay up-to-date with the latest advancements in AI, machine learning, and cloud technologies, and apply this knowledge to improve the GenAI Platform.

What We Are Looking For

• 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Experience operating orchestration systems such as Kubernetes at scale.
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more.
• Proficiency with common programming languages and frameworks of ML, such as Go, Python, etc.
• Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders.
• Strong focus on scalability, reliability, performance, and ease of use.
• Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus.
• Strong proficiency in Python and experience with modern AI/ML frameworks (e.g., LangChain, Vertex AI Agent Builder, TensorFlow, PyTorch) is a plus.

Nice to Have

• Experience with large-scale data processing and storage systems, such as Apache Beam, Apache Spark, or similar technologies.
• Knowledge of containerization technologies, such as Docker, and container orchestration tools, such as Kubernetes.
• Familiarity with agile development methodologies and version control systems, such as Git.
• Experience with cloud-based CI/CD pipelines and automation tools, such as Jenkins or CircleCI.

Benefits and Perks

• Comprehensive Healthcare Benefits and Income Replacement Programs.
• 401k with Employer Match.
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support.
• Opportunity to work on cutting-edge AI and machine learning projects that have a real impact on people's lives.
• Collaborative and dynamic work environment with a team of talented engineers and researchers.
• Flexible working hours and remote work options to ensure a healthy work-life balance.
• Access to the latest technologies and tools to help you stay up-to-date with industry trends.
• Professional development opportunities, including training, mentoring, and conference attendance.

• To stand out as a candidate, make sure your resume and cover letter highlight your experience with cloud-based technologies and ML engineering.
• Prepare to answer behavioral questions that demonstrate your problem-solving skills and ability to work in a team.
• Be ready to discuss your experience with agile development methodologies and version control systems.
• Show a deep understanding of the genAI product development lifecycle and how you can contribute to it.
• Consider creating a portfolio that showcases your work in AI and machine learning, including any personal projects or contributions to open-source repositories.
• Don't be afraid to ask questions during the interview process, such as what the team's vision is for the GenAI Platform or what the biggest challenges are in the role.