Engineering Manager – MLOps & Analytics

About This Opportunity

Our talent team is representing a confidential open-source technology organization in their search for an Engineering Manager to lead MLOps and Analytics initiatives. This is a globally remote role with a focus on building high-performing distributed teams working on machine learning operations platforms and tooling.

We are looking for a technically strong leader who balances hands-on engineering with people management. You'll guide a team working with popular open-source ML tools while fostering growth, collaboration, and technical excellence.

Responsibilities

• Manage and grow a distributed engineering team focused on MLOps and analytics solutions
• Lead team processes, sprint planning, and roadmap execution to achieve ambitious technical goals
• Conduct regular one-on-one meetings with direct reports to support their professional development
• Perform code reviews and provide architectural leadership for ML infrastructure projects
• Collaborate with product managers and peer engineering leaders to define strategy and deliverables
• Monitor team health metrics and drive continuous improvement in engineering practices
• Engage with open-source communities and represent technical work at industry events
• Champion documentation, testing, quality standards, and performance optimization
• Travel 2-4 weeks annually for team gatherings and conferences

What We're Looking For

Required:

• Proven track record in software delivery and team leadership
• Professional Python development experience, preferably with open-source contributions
• Strong understanding of the machine learning landscape and MLOps challenges
• Hands-on experience designing and implementing MLOps solutions
• Exceptional academic background
• Willingness to travel internationally up to 4 times per year

Valued but not required:

• Experience with ML libraries, Kubeflow, MLFlow, Feast, or similar tools
• Track record building highly automated ML solutions for cloud environments
• Experience training or deploying machine learning models
• Proficiency with Docker, Kubernetes, or other container technologies
• Experience with AWS, Azure, or Google Cloud Platform
• Deep familiarity with Linux and open-source ecosystems
• Background working on distributed open-source projects
• Passion for software quality, testing, and automation

How We Work With You

As a recruiting partner, Get A Job.ai connects exceptional talent with leading organizations. When you apply through our platform, a member of our recruiting team will screen your application and conduct an initial conversation about your experience and goals. If there's a strong match, we'll submit your profile to our client for consideration and guide you through their interview process.

Please apply exclusively through Get A Job.ai. Do not contact the client directly, as we manage all candidate communications to ensure a smooth and professional experience.

Pay

Compensation details will be discussed during the screening process and are competitive based on experience and location.

Equal Opportunity: Get A Job.ai is committed to fair hiring practices. We evaluate all candidates based on qualifications and merit, and we encourage applications from people of all backgrounds.