Principal Engineer, Machine Learning Ops

OverviewPrincipal Engineer, Machine Learning Ops: Join our team as a Principal MLOps Engineer and help build the infrastructure and deployment systems for a revolutionary new music discovery platform. You will design and implement scalable, reliable, and efficient systems that support our platform's machine learning models and data pipelines, set up robust development environments for ML engineers, manage model training and experimentation workflows, build and operate data pipelines, and automate deployment of our recommendation systems. Our product is modern, challenging, and ambitious, delivering a first-class, highly engaging user experience that integrates content delivery, audio playback, machine learning, and recommendation systems.What You Will DoOperate in a fast-paced, startup-like environment to launch a new business within Harman.Work with a high degree of autonomy and ownership.Make critical early-stage development decisions to ensure long-term success.Serve as a strong technical voice on backend engineering, ML Engineering, DevOps, and MLOps considerations.Actively engage with product stakeholders in an iterative, dynamic environment.Develop a scalable, maintainable, and operable MLOps infrastructure to support both product launch and future growth.Collaborate closely with app developers and engineers to ensure project success.What You Need To Be SuccessfulExperience: 10+ years across MLOps and DevOpsTechnical Skills: Strong understanding of modern MLOps and DevOps tools and best practices, including model training and deployment, experiment management, scalable data pipelines, and real-time / eventually consistent systems.Programming Languages: Proficient in Python and bashCloud Platforms: Extensive hands-on experience with GCP, AWS, or Azure.Deployment Technologies: Expertise with Docker, Kubernetes, Terraform, and Serverless frastructure Management: Proven experience with data pipelines, infrastructure as code (IaC), monitoring, logging, and alerting systems.System Architecture: Strong knowledge of components such as databases, caches, event streaming, queues, data warehouses, and ML-specific data infrastructure.Automation: Skilled in automating infrastructure, deployments, model training pipelines, and system management using industry-standard tools.MLOps-Specific Skills: Familiarity with setting up robust development environments for ML engineers, managing model experimentation workflows, building and operating data pipelines, and automating end-to-end ML lifecycle management.Bonus Points if You HaveBachelor's degree in computer science or another related field.A passion for music and interest in working on products that bring joy to music lovers worldwide.Experience working with machine learning workloads in productionExperience with social products or recommendation systemsWhat Makes You EligiblePosition is 100% RemoteYou must be available for meetings and team interaction during typical continental US business hours.Be willing to travel up to 5%, domestically and internationally.Successfully complete a background investigation and drug screen as a condition of employment.Seniority levelMid-Senior levelEmployment typeFull-timeJob functionEngineering and Information TechnologyIndustriesComputers and Electronics Manufacturing #J-18808-Ljbffr

Created: 2025-09-17