Senior Machine Learning Ops Engineer

For over half a decade, Hudson Manpower has been a trusted partner in delivering specialized talent and technology solutions across IT, Energy, and Engineering industries worldwide. We work closely with startups, mid-sized firms, and Fortune 500 clients to support their digital transformation journeys. Our teams are empowered to bring fresh ideas, shape innovative solutions, and drive meaningful impact for our clients. If you're looking to grow in an environment where your expertise is valued and your voice matters, then Hudson Manpower is the place for you. Join us and collaborate with forward thinking professionals who are passionate about building the future of work.

Job Title: Senior Machine Learning Ops Engineer
Location: Cincinnati, OH (preferred); Remote USA (EST hours accepted)

What You’ll Do

We are seeking a Senior MLOps Engineer to design, scale, and maintain the Google Vertex AI platform supporting a multi-model recommendation engine. In this role, you’ll build reusable infrastructure, pipelines, and tooling that enable data science and engineering teams to independently deploy and monitor their models.

You’ll collaborate with data scientists, ML engineers, and product teams to ensure models are deployed quickly, securely, and with strong observability. This role is central to delivering enterprise-grade ML services that support personalization, recommendations, and customer engagement.

Key Responsibilities

• Design and maintain reusable templates and modules for model training, deployment, and monitoring

• Build and evolve CI/CD pipelines for ML workflows, enabling rapid experimentation and safe production releases

• Develop tooling for monitoring model performance, drift, latency, and alerting

• Manage and evolve the feature store, model registry, and endpoint management for scalable inference

• Collaborate with domain teams to onboard models, enforce SLAs, governance, rollback/versioning strategies

• Support self-service capabilities by providing platform tooling and guidance

• Ensure integration of models with enterprise services while meeting compliance and governance requirements

• Partner with leadership to define ML platform standards and communicate technical solutions effectively

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

• 4+ years of MLOps experience with ML deployment, monitoring, and scaling in production

• Strong Python development skills

• Proficiency in GCP and Vertex AI; exposure to Azure or hybrid-cloud environments is a plus

• Hands-on with open-source ML frameworks (TensorFlow, PyTorch, scikit-learn)

• Excellent communication and collaboration skills across teams

Top Skills (Must Have)

• 4+ years of experience in MLOps, with expertise in Google Cloud Platform (GCP) and Vertex AI

• Strong proficiency in Python and experience with ML frameworks: TensorFlow, PyTorch, scikit-learn

• Experience designing and supporting CI/CD pipelines for ML workflows

• Hands-on with infrastructure-as-code (IaC) (Terraform, Cloud Deployment Manager, or similar)

• Deep understanding of model deployment, monitoring, and observability
  

Nice to Have

• Exposure to Microsoft Azure or hybrid-cloud ML solutions

• Familiarity with Kubernetes and custom container deployment for ML workloads

• Prior experience supporting recommendation engines or large-scale ML platforms

• Experience leading initiatives and mentoring junior engineers