AI First Machine Learning Engineer

Who We Are

Build. Scale. Sustain.

PALO IT is a global technology consultancy that crafts tech as a force for good. We design, develop and scale digital and sustainable products and services to unlock value across the triple bottom line: people, planet, profit. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

• We are small enough to care locally, big enough to deliver globally (5 continents, 18 offices, +650 experts from +50 nationalities)
• We are robust and resilient (100% independent and 0 debt)
• We are entrepreneurs and passionate experts: We invest in what we believe genuinely and work as a collective intelligence
• We are positive, courageous, caring, doers and committed to excellence

About Gen-e2

While the market is still largely AI-augmenting delivery, we have reinvented the SDLC to be AI First. Our approach is a game-changer in productivity and quality, with a strong collaboration between IA generative and our best Talents:

• We now generate 95% of the entire product — code, documentation, infrastructure as code, and even design — with GitHub Copilot.
• The quality consistently exceeds the output of our best traditional engineering teams.
• A product repository houses all product artefacts, giving AI full project context for higher-quality generation.
• A library of rules and prompts defines coding standards, design principles, and security guidelines, ensuring enterprise-grade quality and scalability.

With Gen-e2, we deliver end-to-end products 2–3× faster than traditional approaches, while raising the bar for engineering excellence.

Your Role

As a Semi Senior Machine Learning Engineer, you will play a key role during the early stages of AI/ML product development, focusing on building reliable ML pipelines, improving deployment processes, and ensuring engineering best practices across the machine learning lifecycle.

You will collaborate closely with Data Scientists, Cloud Engineers, and Software Engineers to industrialize ML solutions, optimize workflows, and support scalable AI deployments in cloud-native environments.

• Design, implement, and maintain scalable Machine Learning pipelines using tools such as Kubeflow, Airflow, and MLflow.
• Support the deployment, monitoring, and optimization of ML models in cloud environments.
• Build production-grade Python services and reusable ML engineering components.
• Containerize and orchestrate ML workloads using Docker and Kubernetes.
• Collaborate with data science teams to transition experiments into robust production solutions.
• Improve CI/CD workflows for ML applications using GitLab CI, Jenkins, Azure Repos, and Git-based development practices.
• Optimize and refactor codebases to improve scalability, maintainability, and performance.
• Ensure security, reliability, and software engineering best practices are applied across ML systems.
• Participate in infrastructure setup and automation for AI platforms on AWS SageMaker and/or GCP AI Platform.
• Contribute to technical documentation, architecture discussions, and continuous improvement initiatives.
• Work within agile and collaborative international teams in an AI-first engineering environment.

Who You Are

• 3+ years of experience in Machine Learning Engineering, MLOps, or Software Engineering roles focused on AI products.
• Strong hands-on experience with Python for production environments.
• Experience implementing ML pipelines using tools such as Kubeflow, Airflow, or MLflow.
• Good understanding of containerization and orchestration technologies (Docker, Kubernetes).
• Familiarity with CI/CD pipelines and version control practices using GitLab CI, Jenkins, Git, or Azure Repos.
• Experience optimizing, refactoring, and maintaining scalable codebases.
• Understanding of software engineering best practices, code quality, and application security principles.
• Exposure to cloud-based ML deployment services such as AWS SageMaker or GCP AI Platform.
• Experience working in agile development environments.
• Strong communication and collaboration skills in multidisciplinary teams.
• Intermediate to advanced English level required for international collaboration.

Nice to Have

• Experience with Infrastructure as Code tools.
• Familiarity with model monitoring and observability tools.
• Knowledge of feature stores and data versioning solutions.
• Exposure to Generative AI or LLMOps ecosystems.
• Experience working in consulting or fast-paced product environments.

AI-Native Engineering (Core Expectation)  

• Use  Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for: 
• Code scaffolding and refactoring
• Code generation and optimisation
• Test-cases and documentation generation
• Build applications through AI-driven development practices , including: 
• AI-assisted debugging and troubleshooting
• Intelligent code completion and pattern recognition
• Automated documentation generation
• Apply prompt engineering best practices for reliable, repeatable engineering outcomes.
• Validate GenAI output (determinism checks, guardrails, fallback logic).

More About PALO IT

We’re eager to adapt to change, learn from our experiences and move to meet our planet’s urgent needs. We are continuously taking action to:

• Become a climate net-zero company
• Deliver projects with a positive impact
• Train 100% of our workforce on impact
• Achieve B Corp certification among all our offices across the globe
• Continuously measure & improve employee happiness

Our clients are amongst the world's most successful companies. We innovate with both established Fortune 1000s, SMEs and start-ups who aim to make an impact, become global leaders and address the world's most complex challenges.

What We Offer

• Stimulating working environments
• Unique career path
• International mobility
• Internal R&D projects
• Knowledge sharing
• Personalized training
• Entrepreneurship & intrapreneurship

For more on our team culture and benefits:

PALO IT is an equal opportunity employer that values merit, qualifications, and abilities. We prioritize privacy and data security. For more information on our privacy practices, please refer to our Privacy Policy.