📍 Job Overview

Job Title: Distributed Cloud | AI Factory
Company: Devoteam
Location: Lisbon, Portugal
Job Type: Full-time
Category: AI & Machine Learning Engineer
Date Posted: 2025-07-31
Experience Level: Mid-Senior level (2-5 years)
Remote Status: On-site (with remote collaboration)

🚀 Role Summary

Develop and implement innovative AI solutions for international projects using the Google Cloud stack.
Work autonomously with significant project freedom and explore new ideas and approaches.
Collaborate closely with multicultural teams, contributing to a dynamic work environment.
Join a specialized team focused on sharing knowledge and professional growth.

📝 Enhancement Note: This role offers a unique opportunity to work on cutting-edge AI projects with significant autonomy and international exposure, fostering professional development and creativity.

💻 Primary Responsibilities

AI Solution Development: Design, develop, and implement AI solutions tailored to diverse international projects, leveraging the Google Cloud stack.
Collaboration: Work closely with colleagues from other countries, fostering a multicultural and dynamic team environment.
Autonomous Project Management: Manage projects with significant autonomy, exploring new ideas and approaches to tackle challenges.
Knowledge Sharing: Contribute to a specialized team by sharing knowledge and driving professional growth.

📝 Enhancement Note: This role requires a strong problem-solving mindset, analytical thinking, and adaptability to handle various projects and challenges effectively.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Relevant master's degrees are a plus.

Experience: Proven experience (2-5 years) in Artificial Intelligence, Machine Learning, or related fields. Experience with the Google Cloud Platform is valued.

Required Skills:

Strong proficiency in AI, ML, or related fields.
Solid knowledge of the Google Cloud Platform (GCP).
Very good English language skills (both spoken and written) for effective communication with international teams.
Ability to work autonomously and proactively.
Flexibility and adaptability to handle different projects and challenges.
Strong problem-solving skills and analytical thinking.

Preferred Skills:

Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Familiarity with cloud-native architecture and microservices.
Knowledge of data engineering and data pipelines.
Experience with Agile methodologies.

📝 Enhancement Note: While not explicitly stated, having experience with AI/ML frameworks, cloud-native architecture, and data engineering would be highly beneficial for this role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A well-structured portfolio showcasing previous AI/ML projects, highlighting your problem-solving skills and technical proficiency.
Live demos or interactive visualizations demonstrating your AI/ML solutions' real-world impact.
Clear documentation explaining your approach, methodology, and results for each project.

Technical Documentation:

Detailed project case studies, including data preprocessing, model selection, training, evaluation, and deployment processes.
Code quality, commenting, and documentation standards, adhering to best practices and industry standards.
Version control, deployment processes, and server configuration management, preferably using GCP services.

📝 Enhancement Note: Given the international nature of the projects, ensure your portfolio and documentation are easily understandable by a global audience.

💵 Compensation & Benefits

Salary Range: €45,000 - €65,000 per year (based on experience and market research for AI/ML roles in Lisbon, Portugal)

Benefits:

Competitive salary package.
Flexible work arrangements, with remote collaboration opportunities.
Multicultural work environment, fostering personal and professional growth.
Equal opportunities and an inclusive work culture.

Working Hours: Full-time (40 hours/week), with flexible working hours and the possibility of remote collaboration.

📝 Enhancement Note: The salary range is estimated based on market research for AI/ML roles in Lisbon, Portugal, considering the experience level and the unique aspects of this role.

🎯 Team & Company Context

🏢 Company Culture

Industry: Devoteam operates in the technology consulting and digital transformation sector, with a strong focus on cloud, data, and cybersecurity services.

Company Size: With over 10,000 employees across more than 20 EMEA countries, Devoteam offers a large, diverse, and multicultural work environment.

Founded: Established in 1993, Devoteam has a rich history and extensive experience in technology consulting and digital transformation.

Team Structure:

The AI Factory team is part of the Distributed Cloud unit, ensuring significant autonomy in day-to-day work and projects.
The team consists of Cloud experts, Business consultants, Security experts, Engineers, Developers, and other multidisciplinary talents.
Collaboration and knowledge sharing are encouraged, fostering a culture of continuous learning and growth.

Development Methodology:

Agile methodologies are used for project management and development processes.
Code reviews, testing, and quality assurance practices are in place to ensure high-quality deliverables.
Deployment strategies, CI/CD pipelines, and server management are handled using GCP services.

Company Website: Devoteam

📝 Enhancement Note: Devoteam's focus on technology consulting and digital transformation creates an environment that values innovation, creativity, and continuous learning, making it an ideal fit for AI and ML professionals.

📈 Career & Growth Analysis

AI & Machine Learning Career Level: This role is at the mid-senior level (2-5 years of experience), offering significant autonomy and international exposure, fostering professional development and growth.

Reporting Structure: The AI Factory team operates within the Distributed Cloud unit, with a flat hierarchy that encourages collaboration and knowledge sharing.

Technical Impact: This role has a significant technical impact, as it involves developing and implementing AI solutions for international projects, driving innovation and digital transformation.

Growth Opportunities:

Technical Growth: Expand your skills and expertise in AI, ML, and GCP services by working on diverse international projects.
Leadership Potential: Demonstrate strong problem-solving skills, technical expertise, and leadership to take on more complex projects and mentor junior team members.
Career Progression: Showcase your achievements and impact in AI/ML projects to progress to senior roles, such as AI Architect or AI/ML Technical Lead.

📝 Enhancement Note: The unique aspects of this role, such as significant autonomy, international exposure, and a focus on innovation, create excellent growth opportunities for AI and ML professionals.

🌐 Work Environment

Office Type: Devoteam's Lisbon office offers a modern, collaborative work environment designed to foster creativity and innovation.

Office Location(s): Av. Dom João II 43, 1990-084 Lisboa, Portugal

Workspace Context:

Collaborative workspace with dedicated areas for team meetings and brainstorming sessions.
Access to modern development tools, multiple monitors, and testing devices to ensure high-quality deliverables.
Flexible work arrangements, with remote collaboration opportunities for better work-life balance.

Work Schedule: Full-time (40 hours/week), with flexible working hours and the possibility of remote collaboration.

📝 Enhancement Note: Devoteam's Lisbon office provides a modern, collaborative work environment that supports the unique needs of AI and ML professionals, fostering creativity and innovation.

📄 Application & Technical Interview Process

Interview Process:

Online Assessment: A technical assessment focusing on AI/ML fundamentals, problem-solving, and coding challenges using GCP services.
Technical Interview: A deep dive into your AI/ML expertise, architecture, and system design discussions, focusing on your problem-solving approach and technical impact.
Behavioral Interview: An assessment of your cultural fit, adaptability, and ability to work autonomously in a multicultural environment.
Final Evaluation: A review of your technical skills, problem-solving abilities, and overall fit for the AI Factory team.

Portfolio Review Tips:

Highlight your AI/ML projects' real-world impact and the challenges you faced during development.
Showcase your problem-solving skills, technical proficiency, and ability to work autonomously.
Demonstrate your ability to collaborate with multicultural teams and adapt to different projects and challenges.
Prepare live demos or interactive visualizations to showcase your AI/ML solutions' performance and user experience.

Technical Challenge Preparation:

Brush up on your AI/ML fundamentals, focusing on problem-solving, data preprocessing, model selection, and evaluation.
Familiarize yourself with GCP services, such as AI Platform, BigQuery, and Cloud Storage.
Practice coding challenges and system design exercises, focusing on your problem-solving approach and architecture decisions.

ATS Keywords: (Organized by category)

Programming Languages: Python, R, Java, C++, Scala
AI & ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM
Cloud Platforms: Google Cloud Platform (GCP), AWS, Azure
Databases: BigQuery, Cloud Spanner, Cloud SQL, PostgreSQL, MySQL
Tools & Libraries: Jupyter Notebooks, Pandas, NumPy, Matplotlib, Seaborn, Plotly
Methodologies: Agile, Scrum, Kanban, Waterfall
Soft Skills: Problem-solving, Analytical thinking, Adaptability, Flexibility, Autonomy, Collaboration, Creativity
Industry Terms: AI, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Data Science, Data Engineering, MLOps

📝 Enhancement Note: The interview process focuses on assessing your technical skills, problem-solving abilities, and cultural fit for the AI Factory team, with a strong emphasis on AI/ML fundamentals, GCP services, and system design.

🛠 Technology Stack & Web Infrastructure

AI & Machine Learning Technologies:

AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM
Cloud Platform: Google Cloud Platform (GCP) – AI Platform, BigQuery, Cloud Storage, Cloud Functions, Cloud Run, Cloud Composer
Programming Languages: Python, R, Java, C++, Scala
Databases: BigQuery, Cloud Spanner, Cloud SQL, PostgreSQL, MySQL
Tools & Libraries: Jupyter Notebooks, Pandas, NumPy, Matplotlib, Seaborn, Plotly, Airflow, Kubeflow, MLflow

Development & DevOps Tools:

Version Control: Git, GitHub, GitLab
CI/CD Pipelines: Jenkins, GitLab CI/CD, CircleCI, Cloud Build (GCP)
Containerization: Docker, Kubernetes, Cloud Run (GCP)
Infrastructure as Code (IaC): Terraform, Cloud Deployment Manager (GCP)
Monitoring & Logging: Prometheus, Grafana, ELK Stack, Cloud Monitoring (GCP), Cloud Logging (GCP)

📝 Enhancement Note: The technology stack focuses on AI/ML frameworks, GCP services, and modern development and DevOps tools, enabling you to work autonomously and develop innovative AI solutions.

👥 Team Culture & Values

AI & Machine Learning Values:

Innovation: Embrace a culture of continuous learning and innovation, driving AI/ML projects that push the boundaries of what's possible.
Collaboration: Foster a collaborative environment that encourages knowledge sharing, mentoring, and teamwork.
Autonomy: Encourage autonomous work and decision-making, empowering team members to explore new ideas and approaches.
Adaptability: Embrace change and adaptability, handling different projects and challenges with flexibility and resilience.

Collaboration Style:

Cross-functional Integration: Collaborate with colleagues from various disciplines, such as business consultants, cloud engineers, and data engineers, to drive AI/ML projects that meet business objectives and user needs.
Code Review Culture: Encourage peer programming and code reviews to ensure high-quality deliverables and knowledge sharing.
Knowledge Sharing: Foster a culture of continuous learning and knowledge sharing, with regular workshops, training sessions, and brown bag lunches.

📝 Enhancement Note: The AI Factory team values innovation, collaboration, autonomy, and adaptability, creating an environment that fosters creativity, technical growth, and professional development.

⚡ Challenges & Growth Opportunities

Technical Challenges:

AI/ML Complexity: Tackle complex AI/ML problems, requiring strong problem-solving skills, architectural design, and optimization techniques.
International Projects: Work on diverse international projects, requiring cultural sensitivity, adaptability, and effective communication with global teams.
Scalability & Performance: Ensure your AI/ML solutions can scale and perform efficiently, handling large datasets and high user loads.
Emerging Technologies: Stay up-to-date with the latest AI/ML trends and emerging technologies, continuously expanding your skill set and expertise.

Learning & Development Opportunities:

AI/ML Specialization: Deepen your expertise in AI/ML by working on diverse projects and collaborating with experienced team members.
GCP Services: Expand your knowledge of GCP services, such as AI Platform, BigQuery, and Cloud Storage, to build scalable and robust AI/ML solutions.
Conferences & Certifications: Attend AI/ML conferences, workshops, and obtain relevant certifications to enhance your professional development.
Mentorship & Leadership: Mentor junior team members and take on leadership roles to drive AI/ML projects and foster a culture of continuous learning.

📝 Enhancement Note: The unique aspects of this role, such as significant autonomy, international exposure, and a focus on innovation, create excellent learning and development opportunities for AI and ML professionals.

💡 Interview Preparation

Technical Questions:

AI/ML Fundamentals: Prepare for questions on AI/ML fundamentals, such as data preprocessing, model selection, evaluation, and optimization techniques.
System Design: Brush up on your system design skills, focusing on architecture, scalability, and performance optimization for AI/ML solutions.
Problem-solving: Demonstrate your problem-solving skills and ability to tackle complex AI/ML challenges effectively.

Company & Culture Questions:

AI Factory Culture: Research the AI Factory team's culture, values, and work environment to demonstrate your fit and enthusiasm for the role.
AI/ML Projects: Prepare for questions about your AI/ML projects, highlighting your problem-solving skills, technical proficiency, and ability to work autonomously.
International Collaboration: Showcase your ability to collaborate with multicultural teams and adapt to different projects and challenges in an international environment.

Portfolio Presentation Strategy:

Live Demos: Prepare live demos or interactive visualizations to showcase your AI/ML solutions' performance, user experience, and real-world impact.
Code Explanation: Practice explaining your code, architecture decisions, and problem-solving approach to demonstrate your technical expertise and communication skills.
User Experience: Highlight the user experience aspects of your AI/ML projects, focusing on accessibility, usability, and performance optimization.

📌 Application Steps

To apply for this AI & Machine Learning Engineer position in the AI Factory team at Devoteam:

Customize Your Portfolio: Tailor your portfolio to highlight your AI/ML projects' real-world impact, problem-solving skills, and technical proficiency.
Optimize Your Resume: Emphasize your AI/ML expertise, problem-solving skills, and experience with GCP services to create a strong resume tailored to this role.
Prepare for Technical Challenges: Brush up on your AI/ML fundamentals, system design skills, and problem-solving abilities to tackle coding challenges and technical interviews.
Research the Company & Team: Familiarize yourself with Devoteam's culture, the AI Factory team's values, and the unique aspects of this role to demonstrate your fit and enthusiasm.

📝 Enhancement Note: This enhanced job description provides comprehensive, web technology-focused content that serves as a valuable resource for AI & Machine Learning professionals seeking their next opportunity and preparing for technical interviews in the AI/ML industry.

Distributed Cloud | AI Factory