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Junior AI Engineer - Hybrid Porto (2-3 days/week on-site)

Porto, Portugal

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Job Openings Junior AI Engineer - Hybrid Porto (2-3 days/week on-site)

About the job Junior AI Engineer - Hybrid Porto (2-3 days/week on-site)

ABOUT THE OPPORTUNITY

Join a leading global staffing technology company with 25+ years of industry leadership, 1,400 professionals across 14 countries, and millions of CVs and jobs processed daily to connect people with the right opportunities. Following a recent strategic acquisition expanding AI capabilities, you'll work on cutting-edge AI systems that read CVs and job advertisements, extract skills and job titles, and match candidates to jobs at a massive scale across multiple languages. 

This is a Junior Software Engineer role with an AI focus, NOT a research position—you'll write production software that ends up in live products used by customers every day, deploying solutions to production and collaborating closely with senior AI engineers. 

Based in Porto with a flexible hybrid model (2-3 days in office), you'll join an established international team of 10 mid-to-senior professionals who will train and mentor your growth. 

The company's people-first culture values Ownership, Energy, Speed & Agility, Service, and Being Human, creating a casual yet fast-paced environment where hard work and outstanding results are rewarded, celebrated, and where leaders care deeply about employee development at all levels.

PROJECT & CONTEXT

You'll help build and run production AI systems that power candidate-job matching at enterprise scale, working with technologies including Python for AI/ML development, FastAPI for building high-performance APIs, and PyTorch for deep learning model implementation. Your work focuses on practical software engineering—not theoretical research—deploying AI capabilities that process massive volumes of CVs and job descriptions across multiple languages and markets. Operating within a Kubernetes environment for container orchestration and scalability, you'll implement CI/CD pipelines using GitLab CI/CD and Jenkins for automated testing and deployment, while working comfortably in Linux environments for development and production operations. 

The role emphasizes shipping production-ready code, not just training models—you'll collaborate with senior engineers to deploy AI features into live customer-facing products, participate in code reviews and pair programming to accelerate your learning, and take ownership of features from conception through production deployment and monitoring. You'll work on challenges including natural language processing for skill extraction (a core focus of this role), entity recognition for job title identification, semantic matching algorithms connecting candidates to relevant opportunities, and building scalable systems that maintain performance under high-volume workloads. The team values individuals who enjoy coding and problem-solving, are curious about AI but grounded in software engineering fundamentals, demonstrate eagerness to learn, and aren't afraid to challenge the status quo with fresh perspectives.

WHAT WE'RE LOOKING FOR (Required)

• Real-World Experience: 1-2 years professional software engineering experience (not fresh from college, but early career)
• Python Proficiency: Solid hands-on Python programming skills for software development and AI/ML applications
• Software Engineering Foundation: Strong coding fundamentals, understanding of software design principles, and clean code practices
• NLP Background (Primary Skill): Practical experience with Natural Language Processing — this is a core requirement for the role; candidates without NLP exposure will not be considered
• ML Model Lifecycle: Hands-on experience building, training, deploying, and monitoring machine learning models in production or near-production environments
• AI/ML Curiosity: Genuine interest in artificial intelligence and machine learning with a desire to apply it to real-world problems
• Production Mindset: Understanding that the goal is shipping working software to production, not just building models
• FastAPI Experience: Practical experience or strong willingness to learn FastAPI for building modern Python web APIs
• PyTorch Knowledge: Familiarity with PyTorch or similar deep learning frameworks (TensorFlow, Keras)
• Problem-Solving Skills: Strong analytical thinking and debugging capabilities for complex technical challenges
• Learning Agility: Eagerness to learn continuously and drive for self-improvement
• Ownership Mentality: Taking responsibility for your work, seeing tasks through to completion
• Collaborative Spirit: Comfortable working closely with senior engineers, asking questions, and accepting feedback
• Adaptability: Thriving in fast-paced, agile environments with changing priorities
• Communication: Clear technical communication skills for discussing code, designs, and challenges with team members
• Language: B2 English (Upper Intermediate) minimum for international team collaboration
• Location: Portuguese nationality or legal right to work in Portugal, based in Porto, with availability for 2-3 days/week on-site

NICE TO HAVE (Preferred)

• Kubernetes Experience: Understanding of container orchestration and deploying applications to K8s clusters
• CI/CD Knowledge: Hands-on experience with GitLab CI/CD, Jenkins, or similar automation tools
• Linux Proficiency: Comfortable working in Linux environments for development and troubleshooting
• NLP Background: Natural Language Processing experience or coursework
• REST API Development: Building and consuming RESTful APIs
• Docker Containerization: Creating and managing containerized applications
• Version Control: Git workflows and collaborative development practices
• Testing Practices: Unit testing, integration testing, and test-driven development
• Cloud Platforms: Azure, AWS, or GCP exposure
• Data Processing: Working with large datasets and data pipelines
• SQL Databases: PostgreSQL, MySQL, or similar relational database experience
• Message Queues: RabbitMQ, Kafka, or similar messaging systems
• Monitoring & Observability: Prometheus, Grafana, or application monitoring tools
• Agile Methodologies: Experience working in Scrum or Kanban teams
• Multiple Languages: Experience working with multilingual data or internationalization
• Vector Databases: Familiarity with Pinecone, Weaviate, or similar vector storage
• Transformer Models: Understanding of BERT, GPT, or similar transformer architectures
• Academic Background: Computer Science, AI/ML, or related technical degree

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