Senior MLOps Engineer

SoftServe; Abu Dhabi; On-site; AED 250,000 - 350,000; Full time

Benefits offered by this job

Access to world-class training and research

Participation in international events

Job summary

SoftServe is looking for an experienced AI/ML expert with a master's degree and over 6 years of relevant experience to join our team in Abu Dhabi. You will work on advanced AI solutions, guide teams through the ML lifecycle, and implement production pipelines.

The ideal candidate should be skilled in Python, CI/CD pipelines, and container orchestration, with an understanding of healthcare data being a significant plus. Join us in shaping the future of AI and make an impact through innovative projects.

Qualifications

• 6+ years of relevant experience.
• Strong in requirements gathering and estimation.
• Demonstrating an upper-intermediate English level.

Responsibilities

• Communicate use cases and requirements to stakeholders.
• Guide engineering and data science teams through the ML systems production lifecycle.
• Collaborate with Data Science teams on model operationalization strategies.
• Implement end-to-end production pipelines for ML solutions.

Skills

Python and traditional data science and machine learning (DS/ML) stack

ML solutions, design patterns, operationalization

AI/ML and data engineering tools in cloud platforms

CI/CD/CT pipelines for ML

Kubeflow or MLflow

Containers and container orchestration platforms (Kubernetes)

Databricks platform

Healthcare data

Education

Master's degree in computer science or related field

Tools

Apache Spark

Airflow

Job description

SoftServe 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 SoftServe’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.

IF YOU ARE

• 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)
• 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

AND YOU WANT TO

• 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

TOGETHER WE WILL

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, DevOps team, and ML Engineers to build infrastructure, set up processes, productize machine learning pipelines, and integrate them into existing business environments

Communicate with the world-leading companies from our logos portfolio

Enjoy the opportunity to work with the latest modern tools and technologies on various projects

Participate in international events and get certifications in cutting-edge technologies

Have access to powerful educational and mentorship programs

Revolutionize the software industry and drive innovation in adaptive self-learning technologies by leveraging multidisciplinary expertise.

SoftServe 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.