Senior MLOps Engineer

About the job
The company is a global digital solutions company, headquartered in Austin, Texas, with a focus on delivering meaningful outcomes through bold thinking and deep expertise. The AI and Data Science Center of Excellence (CoE), primarily based in Europe, serves as the company's premier AI/ML hub, consisting of over 160 experts in various roles such as data scientists, research analysts, MLOps engineers, and ML architects. This center covers the full AI lifecycle, from problem framing to deployment.

In 2024, the CoE delivered over 150 AI projects, with more than 100 focusing on Generative AI, ensuring impactful innovation. Strong collaborations with industry leaders such as NVIDIA, Google Cloud, Amazon, and Microsoft empower teams to work with the latest tools and technologies. A key area of focus in 2025 is Agentic AI, developing autonomous systems to tackle complex, real-world challenges.

Responsibilities

• Communicate use cases, requirements, and expectations with stakeholders
• Guide engineering and data science teams through the ML systems production lifecycle
• Collaborate with Data Science teams on model operationalization strategies
• Work closely with product teams to deliver and operate ML systems
• Implement end-to-end production pipelines for ML solutions
• Support and continuously enhance ML software infrastructure, including CI/CD, data stores, cloud services, network configuration, security, and system monitoring
• Set up scalable monitoring systems for data pipelines and ML models
• Operationalize AI solutions by applying best practices in machine learning, MLOps, DevOps, and software engineering
• Maintain synergy among data scientists, DevOps, and ML Engineers to build infrastructure, set up processes, and productize machine learning pipelines
• Work as a consultant on different projects with a flexible schedule

Requirements

• Master's degree in computer science or a related field
• 6+ years of relevant experience
• Hands-on with Python and traditional Python data science and machine learning (DS/ML) stack
• Expertise in ML solutions, design patterns, and operationalization
• Skilled with AI/ML and data engineering tools in any major cloud platform
• Familiar with setting up continuous integration, continuous delivery, and continuous testing (CI/CD/CT) pipelines for ML
• Well-versed in Kubeflow, MLflow, or similar tools
• Competent with containers and container orchestration platforms (Kubernetes)
• Proficient in Azure cloud services (AI studio, AI search, Azure Data Factory, Azure Functions, Cosmos DB, etc.)
• Experienced with Databricks platform
• Experience working with healthcare data is a plus
• Strong in requirements gathering and estimation
• Experienced with designing and building feature stores
• Knowledgeable of the Hadoop ecosystem and Apache Spark
• Familiar with workflow orchestration platforms such as Airflow
• Upper-intermediate proficiency in English to cover daily project needs

Benefits

• Be part of a team shaping the future of AI and data science through innovation and shared growth
• Advance the frontier of Agentic AI by contributing to intelligent multi-agent ecosystems
• Access to world-class training, cutting-edge research, and top industry partners
• Maintain synergy among Data Scientists, DevOps teams, and ML Engineers to build infrastructure and set up processes
• Opportunity to work with the latest modern tools and technologies on various projects
• Participate in international events and obtain certifications in cutting-edge technologies
• Access to powerful educational and mentorship programs
• Contribute to revolutionizing the software industry and driving innovation in adaptive self-learning technologies

The company is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, age, sex, nationality, disability, sexual orientation, gender identity and expression, veteran status, and other protected characteristics under applicable law.