MLOps Fullstack Engineer

At Optimove, we believe people are capable of more than a single job description. You're not hired just to fill a position- you're empowered to shape it, grow it, and make it your own.

We call this being Positionless.

And Positionless isn't just our culture. It's our product.

Optimove is the creator of Positionless Marketing, an AI-powered platform that gives every marketer the power to analyze, create, launch, and optimize independently. The result is faster execution, deeper personalization, and 88% greater campaign efficiency.

Recognized as a Visionary in Gartner's Magic Quadrant, we partner with leading brands like Sephora, Staples, and Entain. Today, more than 550 Optimovers across NYC, London, Tel Aviv, Scotland, Brazil, Estonia, and beyond are building the future of marketing together, in an environment that actively encourages ownership and growth, with two out of every three managers promoted from within.

If you're looking for a place where you can do more, be more, come grow with us.

Based in Dundee, Scotland, our R&D operation is a dynamic environment, where every developer can impact the flow of technology – from introducing the smallest library to making big infrastructure changes. We welcome open-minded developers who like to share knowledge and help each other to push Optimove forward using the cutting edge of today's tech.

The MLOps team is responsible for the seamless deployment, monitoring, and maintenance of machine learning models in production. Acting as the critical link between the data science and R&D teams, this team will ensure that ML models transition smoothly from development to production, maintaining high availability, scalability, and performance.

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• Managing and optimising existing ML model deployments to ensure reliability and efficiency.
  
• Continuously improving the architecture, processes, and tools used for model deployment, monitoring, and lifecycle management.
  
• Collaborating closely with data scientists to understand and implement model requirements.
  
• Partnering with R&D teams to align technical strategies and integrate ML solutions into broader systems.
  
• Implementing robust CI/CD pipelines, monitoring systems, and infrastructure automation.
  
• Upholding best practices in security, cost management, and infrastructure design for cloud environments.
  

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• Develop and maintain pipelines for model deployment and monitoring.
  
• Collaborate with data scientists to integrate ML models into production systems.
  
• Manage cloud infrastructure and resources for ML workflows.
  
• Assist in automating repetitive tasks and implementing best practices.
  

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• 2+ years of experience in DevOps, MLOps, or a related role.
  
• Proficiency in Python and ML frameworks like TensorFlow or PyTorch.
  
• Familiarity with AWS services (e.g., EC2, S3, SageMaker).
  
• Knowledge of CI/CD tools and workflows.
  
• Basic understanding of containerization (Docker) and orchestration (Kubernetes).
  
• Strong debugging and troubleshooting skills.
  
• Willingness to learn and adapt to new technologies.