MLOps Engineer
Andersen · 4 050–6 000 RUB · Puerto Rico, Palestine, State of, Portugal, Palau, Paraguay, Qatar, Åland Islands, Andorra, The United Arab Emirates, Afghanistan, Antigua and Barbuda, Anguilla, Albania, Armenia, Angola, Antarctica, Argentina, American Samoa, Réunion, Austria, Australia, Aruba, Azerbaijan, Romania, Bosnia and Herzegovina, Barbados, Serbia, Belgium, Burkina Faso, Rwanda, Bulgaria, Bahrain, Burundi, Benin, Saint Barthélemy, Bermuda, Brunei Darussalam, Plurinational State of Bolivia, Saudi Arabia, Solomon Islands, Bonaire, Sint Eustatius and Saba, Seychelles, Brazil, The Sudan, The Bahamas, Bhutan, Sweden, Singapore, Bouvet Island, Saint Helena, Ascension and Tristan Da Cunha, Botswana, Slovenia, Svalbard and Jan Mayen, Belize, Slovakia, Sierra Leone, San Marino, Senegal, Somalia, Canada, Suriname, South Sudan, The Cocos (Keeling) Islands, Sao Tome and Principe, The Democratic Republic of the Congo, El Salvador, The Central African Republic, The Congo, Sint Maarten (Dutch Part), Switzerland, The Syrian Arab Republic, Côte D'ivoire, Eswatini, The Cook Islands, Chile, Cameroon, Colombia, The Turks and Caicos Islands, Costa Rica, Chad, The French Southern Territories, Cuba, Togo, Cabo Verde, Curacao, Christmas Island, Tajikistan, Cyprus, Tokelau, Czech Republic, Timor-Leste, Turkmenistan, Tunisia, Tonga, Turkey, Trinidad and Tobago, Germany, Tuvalu, Tanzania, the United Republic of, Djibouti, Denmark, Dominica, The Dominican Republic, Uganda, Algeria, The United States Minor Outlying Islands, Ecuador, USA, Estonia, Egypt, Western Sahara, Uruguay, Uzbekistan, The Holy See, Eritrea, Saint Vincent and the Grenadines, Spain, Ethiopia, Bolivarian Republic of Venezuela, British Virgin Islands, U.S. Virgin Islands, Vanuatu, Finland, Fiji, The Falkland Islands (Malvinas), Federated States of Micronesia, The Faroe Islands, France, Wallis and Futuna, Gabon, The United Kingdom of Great Britain and Northern Ireland, Samoa, Grenada, Georgia, French Guiana, Guernsey, Ghana, Gibraltar, Greenland, The Gambia, Guinea, Guadeloupe, Equatorial Guinea, Greece, South Georgia and the South Sandwich Islands, Guatemala, Guam, Guinea-Bissau, Guyana, Kosovo, Hong Kong, Heard Island and Mcdonald Islands, Honduras, Croatia, Yemen, Haiti, Hungary, Mayotte, Ireland, Israel, Isle of Man, India, The British Indian Ocean Territory, South Africa, Iceland, Italy, Zambia, Jersey, Zimbabwe, Jamaica, Jordan, Japan, Kenya, Kyrgyzstan, Cambodia, Kiribati, The Comoros, Saint Kitts and Nevis, Korea Republic, Kuwait, The Cayman Islands, Kazakhstan, The Lao People's Democratic Republic, Lebanon, Saint Lucia, Liechtenstein, Liberia, Lesotho, Lithuania, Luxembourg, Latvia, Libya, Morocco, Monaco, The Republic of Moldova, Montenegro, French Part Saint Martin, Madagascar, The Marshall Islands, North Macedonia, Mali, Myanmar, Mongolia, Macao, The Northern Mariana Islands, Martinique, Mauritania, Montserrat, Malta, Mauritius, Maldives, Malawi, Mexico, Malaysia, Mozambique, Namibia, New Caledonia, The Niger, Norfolk Island, Nigeria, Nicaragua, The Netherlands, Norway, Nepal, Nauru, Niue, New Zealand, Oman, Panama, Peru, French Polynesia, Papua New Guinea, Poland, Saint Pierre and Miquelon, Pitcairn · сайт компании
Описание вакансии
Andersen is hiring an MLOps Engineer for a project building a scalable ML platform on AWS and Databricks, supporting model lifecycle, automation, and reliable production operations.
The customer is a global digital platform in the urban services domain, operating a high-load marketplace that connects users and service providers in real time. The platform focuses on scalability, reliability, and data-driven product development, leveraging distributed systems and mobile technologies to support dynamic pricing and large transaction volumes across multiple regions.
The project is focused on building a scalable, secure, and automated ML platform on AWS and Databricks. It supports the full ML lifecycle, including data processing, model training, deployment, monitoring, and retraining, with strong emphasis on MLOps, automation, and production-grade reliability.
Responsibilities
Designing and implementing scalable, secure, and cost‑efficient MLOps solutions leveraging AWS and Databricks.
Automating ML deployment pipelines, reducing manual intervention and operational overhead.
Collaborating closely with data scientists to ensure solutions align with established MLOps architecture, best practices, and platform standards.
Integrating security controls and compliance requirements throughout the entire machine learning lifecycle.
Owning and managing incidents end‑to‑end, from root cause analysis to prevent future occurrences.
Contributing to software system architecture and the design of platform‑level components.
Building and optimizing ML training, retraining, and inference pipelines, ensuring reliability and scalability.
Enhancing observability with metrics, logging, tracing, and dashboards to ensure system visibility and performance.
Driving best practices in infrastructure automation, CI/CD, and cloud resource management across ML teams.
Requirements
Experience as an MLOps Engineer or in a similar role for 4+ years.
Strong hands‑on experience with AWS architecture, including security best practices, IAM, networking, and cost optimization.
Proficiency with Databricks: MLflow, Workflows, Feature Store, cluster management, Unity Catalog.
Experience with cloud‑managed ML platforms such as AWS SageMaker or Google Vertex AI.
Expert knowledge of Terraform / Terragrunt for multi‑cloud infrastructure provisioning and automation.
Deep expertise in Kubernetes, including autoscaling, GPU workloads, networking policies, and cluster optimization.
Practical experience with observability stacks such as Prometheus, Grafana, Loki, ELK.
Strong understanding of GitOps workflows and CI/CD tools (e.g., ArgoCD, FluxCD).
Solid knowledge of Docker security, container hardening, and secure container orchestration.
Advanced experience in MLOps practices for continuous training (CT), CI/CD for ML models, and automated deployment.
Familiarity with ML pipeline orchestration tools such as Kubeflow or Argo Workflows.
Experience with LLMOps, including frameworks such as Langfuse, ollama, vLLM, and supporting large‑scale inference.
Ability to contribute to architecture design, set platform standards, and mentor MLOps or ML engineers.
Level of English – from Intermediate+ and above.
Why join us
Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc..
The opportunity to change the project and/or develop expertise in an interesting business domain.
Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.
Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.
The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
Certification compensation (AWS, PMP, etc).
Referral program.
Private health insurance and compensation for sports activities.
Join us!