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Associate Director, MLOps Engineering

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Hybrid

Associate Director, MLOps Engineering

Ladders

Associate Director, MLOps Engineering

Skills

Google Cloud PlatformData ScienceMachine LearningAIAWSKubernetesAzure

20 days ago

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Important information


Contract type:

Permanent

Location:

United States

Work mode:

Hybrid

Published on:

4 October 2026

What they need


For our client, we are seeking a Associate Director, MLOps Engineering to join the team of a leader in the Healthcare space.

This role will shape the vision and execution of the machine learning operations function, with a focus on scalable infrastructure, production inference, and platform adoption. You will lead a team of engineers while partnering closely with machine learning, data science, infrastructure, and site reliability stakeholders to remove bottlenecks and improve system performance. The position will also help modernize the company's AI product inference stack and strengthen the technical foundation needed to support growth at scale.

Location: Remote - US based candidates only, no visa sponsorship available

Compensation: $181,500 – $278,300 annually

Responsibilities

  • Develop and execute the long-term vision and roadmap for the MLOps team
  • Lead and mentor a team of 6-7+ engineers and manage resources for existing services
  • Partner with leaders across machine learning, data science, and infrastructure to address bottlenecks
  • Architect compute and storage pipelines for ML engineers managing large datasets
  • Modernize the AI product inference stack to support significant growth
  • Collaborate with Site Reliability Engineering to establish comprehensive metrics
  • Conduct build-vs-buy assessments for benchmarking proprietary tools

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience
  • 8-10+ years of experience in Software/ML Engineering, including 4+ years managing engineering teams
  • Proven track record of growing engineering teams and driving MLOps platform adoption
  • Deep technical expertise with ML workloads on Kubernetes and cloud computing platforms, including AWS, GCP, or Azure
  • Experience managing petabyte-scale datasets and high-throughput production inference pipelines
  • Strong software engineering skills in complex, multi-language systems
  • Experience using AI assistants across platform development lifecycles

Benefits

  • Hybrid work environment
  • Opportunity to lead high-impact and high-growth strategic initiatives
  • Mentorship and development of engineering talent
  • Access to cutting-edge technology in ML infrastructure
  • Direct involvement in organizational growth and system scalability

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.

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