Senior MLOps Engineer

WE ARE

Soft Serve is a global digital solutions company, headquartered in Austin, Texas, and founded in 1993.

With 2,000+ active projects across the USA, Europe, APAC, and LATAM, we deliver meaningful outcomes through bold thinking and deep expertise. Our people create impactful solutions, drive innovation, and genuinely enjoy what they do.

The AI and Data Science Center of Excellence (CoE) is Soft Serve's premier AI/ML hub, primarily based in Europe. With 160+ experts, including data scientists, research analysts, MLOps engineers, ML and LLM architects - we cover the full AI lifecycle, from problem framing to deployment.

In 2024, we delivered 150+ AI projects, including over 100 focused on Generative AI, combining scale with measurable impact.

We are a 2024 NVIDIA Service Delivery Partner and maintain strong collaborations with Google Cloud, Amazon, and Microsoft, ensuring our teams always work with cutting-edge tools and technologies.

We also lead Gen AI Lab - our internal innovation engine focused on applied research and cross-functional collaboration in Generative AI.

In 2025, a key area of innovation is Agentic AI, where we design and deploy autonomous, collaborative agent systems capable of addressing complex, real-world challenges at scale for our clients and internally.

• A holder of a master's degree in computer science or a related field
• Having 6+ years of relevant experience
• Hands-on with Python and traditional Python data science and machine learning (DS/ML) stack
• An expert 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
• 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 - it would be 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
• Demonstrating an upper-intermediate English level to cover daily project needs

• 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, Dev Ops, and software engineering
• Maintain synergy among data scientists, Dev Ops, 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

Be part of a team that's shaping the future of AI and data science through innovation and shared growth.

Advance the frontier of Agentic AI by shaping intelligent multi-agent ecosystems that drive autonomy, scalability, and measurable business value.

Have access to world-class training, cutting-edge research, and collaborate with top industry partners.

Maintain a synergy of Data Scientists, Dev Ops team, and ML Engineers to…