Open Positions

About us

At Programize, we partner with teams of all sizes - from startups to established enterprises - across industries and continents to create innovative, high-impact software products. We don’t just implement requirements; we turn ambitious ideas into marketable software solutions we are genuinely proud to put our names on. With 200+ successfully delivered projects behind us, we’ve tackled everything from greenfield architectures to complex, large-scale platforms.

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Our vision is to become the go-to company for entrepreneurs and engineers, who want to design and develop impactful, scalable software systems. 

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To achieve that, we need talented professionals to join our team, to share the thrill for technology and innovation.

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The Role

Our team is collaborating with a company that aims to pioneer the future of play at one of the world's largest, most beloved toy companies and communities and we are looking for an experienced DevOps / MLOps Engineer who will own and lead DevOps across the department, supporting both the model training and inference infrastructure as well as the customer-facing applications. 

You will play a critical role in architecting, scaling, and maintaining the infrastructure that powers  frontier models, and design systems that enable seamless training, evaluation, and deployment of cutting-edge AI models - ensuring reliability, performance, and safety at every stage of the lifecycle. 

You will also manage and scale the production environments that support customer-facing applications, internal services, and AI systems, ensuring consistency, reliability, and operational excellence across all platforms.

What You Will Do

• Architect, manage and build cloud-based infrastructure (AWS, GCP, or Azure) optimized for large-scale distributed training as well as inference in scale.

• Architect, manage and build cloud-based infrastructure for the backend of our consumer based applications.

• Develop and maintain ModelOps pipelines for continuous training, testing, and deployment of frontier models.

• Design, build, and maintain CI/CD pipelines for large-scale AI and model development.

• Implement monitoring, observability, and rollback systems for AI services in production.

• Collaborate closely with ML engineers and researchers to streamline experimentation and model delivery.

• Develop infrastructure automation using tools such as Terraform, Kubernetes, and Docker.

• Establish best practices for reliability, security, and AI safety compliance within the model lifecycle.

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What You Have

• 5+ years of experience in DevOps, MLOps, or infrastructure engineering for ML systems.

• Proven experience managing large-scale training and inference pipelines in production.

• Deep expertise in Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).

• Strong background with Infrastructure as Code tools (Terraform, etc.).

• Proficiency in Python and scripting (Bash or similar).

• Experience with CI/CD systems (GitHub Actions, GitLab CI, Jenkins, etc.).

• Familiarity with ML lifecycle tools such as MLflow, Kubeflow, Airflow.

• Familiarity with cloud specific ML tools such as Sagemaker or Vertex.AI.

• Excellent problem-solving and debugging skills across complex distributed systems.

• Familiarity with monitoring and observability stacks (Prometheus, Grafana, etc.).
   

Nice to have

• B.Sc. or above in Computer Science, Software Engineering, or a related field.

• Strong understanding of data management, artifact storage, and model governance.

• Previous experience in early-stage teams or founding technical roles.
   

What to expect from us
Programize was founded on the values of respect and appreciation for customers and colleagues alike. We believe in equal opportunity, diversity, flexibility, hard work and continuous improvement in all aspects of our company. We want our people to feel happy, creative, productive and motivated. So, in Programize you will find the following:

• Friendly, respectful and appreciative working environment.

• Competitive remuneration package.

• On-site and remote working options.

• Lab-like, collaborative, and engaging environment

• Continuous learning and growth opportunities.

• International working environment.

• Work-life balance.

• Private health insurance plan, including dependents.
   

 

Disclaimer:
Programize collects and processes personal data in accordance with the EU General Data Protection Regulation (GDPR). We are bound to use the information provided within your job application for recruitment purposes only and not to share these with any unauthorized third parties, and all applications will be treated as strictly confidential.