MLOps Team Lead

Description

For many of us there’s that one podcast we never miss, and video content is part of our daily routine, whether it’s professional or personal. But how many of us truly understand the effort that goes on behind the scenes? Here at Riverside, we know it well. That’s exactly why we built an AI-powered platform that helps content creators, podcasters, marketeers, and more at major brands like Netflix, Disney, Google, and Microsoft to create high-quality content with ease.

Riverside’s technology streamlines the entire content creation process, turning ideas into professional-grade content with the highest production standards, without requiring expensive equipment or external services. The secret? AI-driven tools that replace traditional production roles like editing, directing, and design, automating the entire process at the click of a button.

About the Innovation Team

At Riverside, the Innovation team is all about pushing the limits of AI to transform content creation. We work on everything from enhancing audio and video quality to automating production with machine learning, NLP, and computer vision. Whether it’s real-time rendering, intelligent editing, or new ways to process media, we turn cutting-edge research into practical tools that creators rely on. If you’re excited about shaping the future of media tech, you’ll fit right in.

On your day to day

This is a technical leadership role that combines hands-on engineering, strategic vision and team management. You will define MLOps best practices, build high-performance infrastructure for development and production, and recruit, mentor and lead a team of world-class professionals.

You will work at the intersection of AI research and production systems, collaborating closely with AI Researchers, ML Engineers, and other stakeholders. Your impact will be measured in accelerating AI innovation at Riverside through fast, scalable, and reliable ML infrastructure and workflows. Your work will touch a broad range of cutting-edge technologies, covering everything from distributed training orchestration to real-time inference optimization.

Roles and Responsibilities

• Lead the development of scalable ML pipelines, CI/CD workflows and orchestration infrastructure to support AI model development at scale in a multi-cloud setting.
• Work closely with AI researchers, ML Engineers, Backend Engineers and DevOps teams to develop MLOps infrastructure and best practices that address real-world needs.
• Recruit, grow and mentor a high-impact MLOps team, driving a culture of technical excellence and good vibes.
• Own distributed compute environments for AI model training and inference on large-scale GPU clusters.
• Build supporting data infrastructure such as data pipelines, feature stores and large-scale storage.
• Develop solutions for GPU resource allocation, utilization monitoring and optimization.
• Implement A/B testing, canary releases and rollback mechanisms for model deployment.
• Develop robust monitoring, logging and alerts for model performance and reliability.

Requirements

What Will Make You Stand Out?

• 6+ years of experience in Backend Engineering / MLOps / Platform Engineering.
• BSc in Computer Science, Software Engineering or related field.
• Experience as Team Lead (or equivalent software development management positions).
• Strong software engineering skills in Python with an emphasis on writing clean, maintainable, and scalable code.
• Proven track record of building production-grade, large-scale backend systems.
• Strong grasp of system architecture principles.
• Hands-on experience in ML pipeline automation and large-scale model deployment.
• Deep understanding of Docker, Kubernetes, cloud-native architectures (AWS/GCP) and infrastructure as code (Terraform, Helm, ArgoCD).
• Proficiency in modern CI/CD best practices and tools (GitHub Actions or similar).
• Experience with observability & monitoring stacks (Prometheus, Grafana, Coralogix).
• Experience with workflow orchestration engines (such as Airflow, Argo Workflows or  Temporal).
• Experience with distributed processing platforms (Apache Kafka or similar).

Leadership

• Proven ability to lead high-impact engineering teams in a fast-paced R&D environment.
• Hands-on mindset with a developed sense of ownership and a bias for action.
• Passion for mentorship, team-building and fostering a culture of innovation.
• Strong cross-functional collaboration skills, ability to work closely with researchers, engineers and other stakeholders.
• Proven ability to drive technical decisions, weighing short-term and long-term considerations, executing risk reduction and taking smart bets.
• Excellent verbal and written communication skills

Bottom line? If you have deep technical expertise, thrive in fast-paced, innovative environments, and are excited by the challenge of building a formidable MLOps team, we want to hear from you.