Lead MLOps Engineer
We are a team of experts, bringing together the best talents in IT and analytics. Our mission is to provide innovative solutions through our flagship service, which includes forming tech teams from scratch and expanding existing units, all tailored to help our partners become truly data-driven organizations.
Currently, we are looking for a Lead MLOps Engineer to support our partner in developing a Global Analytics unit — a centralized team dedicated to strengthening data-driven decision-making and creating smart data products for day-to-day operations.
We are looking for an experienced technical leader who enjoys shaping engineering direction, scaling AI-powered products, and driving technical excellence across globally deployed analytics solutions.
About the Team
The Global Analytics team is an innovative and diverse collective of Data Scientists, Data Engineers, ML Engineers, MLOps Engineers, Business Intelligence Specialists, Software Developers, UX Designers, and more, with a presence across three continents and five countries.
The team drives innovation and reliability while transforming the organization into a truly data-driven enterprise.
One of the products developed by the Global Analytics team is an AI-powered sales and analytics ecosystem — a sophisticated, multi-module product suite delivering intelligent capabilities that support global commercial operations and business decision-making.
Examples of capabilities include:
Consumer behavior change alerts identifying where immediate actions should be taken
Route optimization supporting field and sales teams
Product recommendation engines
Forecasting and optimization solutions
Intelligent insights supporting sales effectiveness
And many more advanced AI-powered capabilities
As analytics capabilities continue to scale globally, we are looking for a Lead MLOps Engineer to take ownership of technical direction, engineering excellence, and operational reliability across this complex AI-driven product landscape.
What We Offer
High-impact projects involving advanced analytics and AI initiatives
Opportunity to work in a global and diverse team with international reach
Ownership over technical direction and the opportunity to shape engineering standards across globally deployed AI solutions
Opportunity to influence architecture and long-term technology strategy for a complex AI-powered product ecosystem
Work on sophisticated, business-critical AI products used in real-world commercial operations
Exposure to large-scale, production-grade AI systems operating across global markets
Casual atmosphere with no unnecessary corporate bureaucracy
Continuous learning opportunities, certifications, knowledge-sharing initiatives, and online courses
Responsibilities
Own technical direction and operational excellence of complex AI-driven business solutions deployed globally
Define architecture and engineering standards for scalable production-grade AI applications
Shape engineering and MLOps best practices across a multi-module analytics product ecosystem
Lead and coordinate technical teams toward sprint goals and delivery excellence
Partner with Product Owner to translate business priorities into technical roadmaps and engineering initiatives
Guide teams in architectural decisions across interconnected AI, data, and application components
Drive technical decision-making and establish engineering standards across ML and software teams
Review technical solutions and pull requests to ensure maintainability, scalability, and operational reliability
Support teams in improving engineering practices and delivery effectiveness
Design cloud-native architectures supporting AI-powered business products
Ensure AI solutions are observable, scalable, maintainable, and production-ready
Own deployment standards, monitoring approaches, lifecycle management, and reliability practices for AI-driven applications
Collaborate closely with Data Scientists, Data Engineers, and Software Engineers to operationalize intelligent business solutions
Support engineering teams in integrating AI services, APIs, pipelines, and business-facing application components
Drive standardization and continuous improvements across the AI product landscape
Qualifications and Experience
Advanced degree in Computer Science, Engineering, Mathematics, or related STEM field
5+ years of experience in MLOps, ML Engineering, Platform Engineering, or software engineering supporting ML systems in production
Strong understanding of machine learning concepts and experience operationalizing ML solutions at scale
Strong Python software engineering background
Experience designing, deploying, and scaling complex AI-driven applications in production environments
Experience with ML frameworks such as TensorFlow or PyTorch and MLOps tools such as MLflow
Strong understanding of CI/CD principles and MLOps practices
Experience designing scalable ML deployment and orchestration architectures
Expertise in DevOps technologies including Docker and Kubernetes
Strong Azure experience and familiarity with services such as Azure Machine Learning, Databricks, Azure Data Factory, or equivalent cloud tools
Experience working with large-scale distributed data environments (e.g., PySpark)
Strong understanding of software architecture and engineering design patterns
Experience with Git and Agile environments
Ability to communicate effectively with both technical and business stakeholders
Professional and service-oriented mindset
Fluent English
Business Impact
The solutions delivered in this role directly support global business operations by enabling scalable and reliable AI systems, accelerating delivery of intelligent products, and ensuring operational excellence across complex business-critical solutions.
Role Breakdown
60% leadership, team coordination, stakeholder management, and technical ownership
40% architecture, technical reviews, engineering strategy, and platform direction
If you enjoy shaping engineering culture, driving MLOps excellence, and building sophisticated AI products operating at global scale, we would love to hear from you.
Apply now!
Please add to your CV the following clause:
"I hereby agree to the processing of my personal data included in my job offer by hubQuest spółka z ograniczoną odpowiedzialnością located in Warsaw for the purpose of the current recruitment process.”
If you want to be considered in the future recruitment processes please add the following statement:
"I also agree to the processing of my personal data for the purpose of future recruitment processes.”
Lead MLOps Engineer
Lead MLOps Engineer