Principal Engineer, Machine Learning Ops
US Home Office California
HARMAN International
HARMAN International is a global leader in connected car technology, lifestyle audio innovations, design and analytics, cloud services and IoT solutions.General information
Location: US Home Office California Worker Type Reference: Regular - Permanent Pay Rate Type: Salary Career Level: T4 Job ID: R-43694-2025 Apply
Description & Requirements
About the Role
Join our team as a Principal MLOps Engineer and help build the infrastructure and deployment systems for a revolutionary new music discovery platform. You'll play a critical role in designing and implementing scalable, reliable, and efficient systems that support our platform's machine learning models and data pipelines. This includes setting up robust development environments for ML engineers, managing model training and experimentation workflows, building and operating data pipelines, and automating 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. Join us in transforming the world of music consumption.
What You Will Do
- Operate 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 Successful
- Experience: 10+ years across MLOps and DevOps
- Technical 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 bash
- Cloud Platforms: Extensive hands-on experience with GCP, AWS, or Azure.
- Deployment Technologies: Expertise with Docker, Kubernetes, Terraform, and Serverless architectures.
- Infrastructure 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 Have
- Bachelor'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 production
- Experience with social products or recommendation systems
What Makes You Eligible
- Position is 100% Remote
- You 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.
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Pay Transparency
$ 113,250 - $ 166,100
Dependent on the position offered, other forms of compensation are also available, such as bonuses or commission.
Pay is based on a wide range of factors, including, without limitation, skill set, experience, training, location, and business need. While the above range is a reasonable estimate of the wage range for this position, please note the disclosed range estimate has not been adjusted for the applicable geographical differential associated with the location where the position may be filled.
BenefitsHARMAN is interested in the health and wellbeing of you and your family and offers a range of benefits designed to support your needs for holistic wellbeing. Benefits and perks may vary depending on the nature of your employment with HARMAN, and may include paid vacation and holidays, paid sick leave, volunteer leave, and paid bonding and care giver leave. Employees may also be eligible to participate in comprehensive medical, dental, and vision plans, fertility support and adoption assistance, Health Savings and Flexible Spending Accounts, retirement savings plan with employer match, short and long term disability coverage, life insurance, and more.
Important Notice: Recruitment Scams Please be aware that HARMAN recruiters will always communicate with you from an '@harman.com' email address. We will never ask for payments, banking, credit card, personal financial information or access to your LinkedIn/email account during the screening, interview, or recruitment process. If you are asked for such information or receive communication from an email address not ending in '@harman.com' about a job with HARMAN, please cease communication immediately and report the incident to us through: harmancareers@harman.com.
HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Apply
Tags: Architecture AWS Azure Banking Computer Science Data pipelines DevOps Docker Engineering GCP Kubernetes Machine Learning ML models MLOps Model training Pipelines Python R Streaming Terraform
Perks/benefits: Career development Fertility benefits Flex hours Flexible spending account Flex vacation Health care Home office stipend Insurance Medical leave Salary bonus Startup environment
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