hubQuest
Távmunka
2.8M – 3.2M HUF vállalkozói havonta+ÁFA
Elvárások
- MLOps
- Azure
- Production ML / ML Engineering
- Software Architecture
- CI/CD
- Python
- Docker
- Kubernetes
- MLflow
- Databricks
- PySpark
- TensorFlow
- PyTorch
- Angol (C1)
- Lengyel (C1)
A mi követelményeink
Eredeti szöveg. Fordítás megjelenítése
- 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
Pozíció / projekt rövid leírása
Eredeti szöveg. Fordítás megjelenítése
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
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!
Napi feladatok
Eredeti szöveg. Fordítás megjelenítése
- 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
mutass kevesebbet
Specifikációk
- Online állásinterjú
- Toborzás nyelvei: angol&lengyel
- Azonnali kezdés
- Távmunka
- Rugalmas munkaidő
- Nem jár utazással
- Főleg új funkciók
Biztosított eszközök
- Apple
- Windows
- Számítógép: Notebook
- as many as you need 🙂
Metodológia
- Agile managementScrum, Agile
- Issue tracking tool
- Knowledge repository
- Cloud infrastructureAzure
- Version control system
- Code reviews
- Munkaeszközök kiválasztásának lehetősége
Extrák
- Nemzetközi projektek
