Senior DevOps/MLOps Engineer

<p><br><strong>We are looking for a Senior DevOps/MLOps Engineer:</strong></p><p><strong>Tech Level:</strong> Senior</p><p><strong>Language Proficiency:</strong> Upper-Intermediate</p><p><strong> Employment type:</strong> Full time</p><p><strong>Candidate Location:</strong> Not Russia, Not Belarus, Not Ukraine</p><p><strong>Working Time Zone:</strong> CET</p><p><strong>Planned Work Duration:</strong> 6 months</p><p><strong>👥 Customer Description:</strong></p><p>A global mobility and urban services platform that allows users to book rides or other services and negotiate the fare directly with service providers. It offers a variety of services including ride-hailing, intercity travel, delivery, and task assistance, operating across multiple cities and countries and is one of the most popular mobility apps globally.</p><p><strong>⚙️ Project Phase:</strong> New phase of the project</p><p><strong>🤝 Soft Skills:</strong></p><p>• Highly proactive with the ability to independently identify stakeholders and drive tasks to completion</p><p>• Strong stakeholder management skills with the ability to interact effectively across different seniority levels</p><p>• Curious mindset with a focus on continuous improvement and challenging existing processes</p><p>• Excellent communication skills for effective collaboration with cross-functional teams</p><p>• Strong time management skills with a high level of organization and reliability</p><p>•<span> </span>Russian language is a must</p><p></p><p><strong>💡 Hard Skills / Must Have:</strong></p><p>• Experience with AWS architecture, security best practices, and cost optimization</p><p>• Proficiency with Databricks</p><p>• Experience with cloud-managed ML platforms such as AWS Sagemaker or Google Vertex AI</p><p>• Expert knowledge of Terraform or Terragrunt for multi-cloud infrastructure management</p><p>• Strong expertise in Kubernetes including cluster scaling and advanced networking concepts</p><p>• Hands-on experience with observability tools such as Prometheus, Grafana, Loki, or ELK</p><p>• Deep knowledge of Git-based workflows and CI/CD tools such as ArgoCD or FluxCD</p><p>• Strong understanding of Docker security and container orchestration</p><p>• Advanced skills in MLOps for continuous retraining and deployment</p><p>• Experience with ML pipeline tools such as Kubeflow or Argo Workflow</p><p>• Experience with LLMOps frameworks such as Langfuse, ollama, or vLLM</p><p></p><p><strong>📌 Responsibilities and Tasks:</strong></p><p>• Design and implement scalable, secure, and cost-effective MLOps solutions on cloud platforms</p><p>• Automate deployment pipelines and reduce manual effort</p><p>• Collaborate with data scientists to align solutions with MLOps architecture and best practices</p><p>• Integrate security throughout the machine learning lifecycle</p><p>• Manage issues from root cause analysis to resolution and provide feedback for prevention</p><p>• Contribute to system architecture and software design</p><p><strong>🧪 Technology Stack:</strong> AWS, AWS Sagemaker, Databricks</p><p><strong>📞 Interview stages:</strong></p><p>• English check (15 minutes)</p><p>• internal technical interview (1-1,5hour)</p><p>• client interview (1 hour)</p><p>• client interview – team fit (45 minutes)<br><br><strong>📩 Ready to Join?</strong><br>We look forward to receiving your application and welcoming you to our team!</p>