Senior Machine Learning Engineer Ship models that move the business, not just the metrics.

Love what you do – we make employment happen!

Are you a passionate Senior Machine Learning Engineer eager to take on a new challenge that has the potential to revolutionize the European Job Ads Market? Then keep reading!

We're seeking a Senior Machine Learning Engineer to join our cross\-departmental Data Science unit. In this high\-impact role, you'll work across multiple teams and projects throughout the organization, leading the development and deployment of production ML systems that serve diverse business needs. As a senior member of our team, you'll be responsible for architecting scalable ML infrastructure, mentoring team members, and driving technical excellence as we transform data science prototypes into robust production services that deliver value across the enterprise.

We are JobCloud, Switzerland nº 1 brand and experts in the job ads market, and we seek your expertise, ideas, and human skills to build our brand new software while cultivating our dearest value “Love what you do.” in our newly established company in Porto, Portugal \- known as JobCloud HR Tech Unipessoal Ltd.

A decade ago JobCloud conceived a concept ahead of its time \- a product designed to efficiently manage and optimize the usage of the customer’s hiring budget while identifying the optimal channels to maximize the visibility of job ads (AI/ML are key to optimizing this process) and effectively reach the target public (potential employees).

Today our mission is to revolutionize the industry standard shifting away from the current job ads paradigm of Pay per Duration toward Pay per Performance. What was once merely a concept is now on the cusp of becoming a reality!

• Porto


• Permanent


• IT


• 01\.05\.2026


• Full\-time

YOUR TASKS

• Partnering with Data Science to translate experimental models into scalable, production\-grade ML systems


• Designing and build high\-performance, low\-latency model\-serving architectures and infrastructure


• Defining and enforce best practices for ML productionization, including coding standards, testing, and deployment strategies


• Leading cross\-functional collaboration between Data Science, Engineering, and Operations as the primary technical interface


• Defining and implementing model performance monitoring (e.g., drift detection, data quality, inference metrics) to ensure reliability in production


• Driving innovation by evaluating new tools, frameworks, and methodologies, and promoting their adoption across the organization


• Developing and maintain technical documentation, system designs, and operational runbooks.

YOUR SKILLS

• 5\+ years of experience in ML Engineering, MLOps, or closely related roles


• Proven experience deploying and maintaining machine learning models in production at scale


• Strong Python skills, including experience with data and ML ecosystems


• Familiarity with LLMs, RAG, and emerging AI paradigms (e.g., agent\-based systems)


• Hands\-on experience with cloud platforms (e.g., AWS) for building and operating ML systems


• Experience with containerization (Docker) and building production\-ready services


• Demonstrated ability to lead technical projects and make architectural decisions


• Full professional proficiency in English

OUR OFFER

• 1 day per month to tackle challenges inside the project, or test new ideas


• Tech training and human skills training and, budget for conferences


• Opportunity to travel and collaborate in our various office locations for workshops or team\-building events (Zurich, Geneva, Belgrade or Vienna)


• A dynamic work environment that highly fosters a sense of fun while maintaining a productive atmosphere

• 10 days fully paid sick leave per year


• 25 days of annual vacation leave


• Full private health coverage (employee \+ up to 2 children to age 20\)


• Gym allowance


• Workation


• Hybrid \& flexible working (team\-based arrangement)

YOUR CONTACT PERSON

• Presentation of the project and company (30 mins)


• Conversation with hiring manager (1 hour)


• Technical challenge (at your best convenience)


• Challenge presentation (1h\-1\.5 hour)


• Offer

*Head of Operations*

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