The Role
Design, build, and optimize scalable data pipelines and ML/AI frameworks. Develop, train, deploy, and tune ML models (including NLP, computer vision, recommender systems) at enterprise scale. Apply GenAI tools, ensure data governance, security, and performance, support AI infrastructure and platform deployments, and contribute to CoE standards and reusable frameworks.
Summary Generated by Built In
As a Senior AI/ML Engineer , you will:
- Design, develop, and optimize data pipelines and workflows supporting advanced analytics and AI/ML solutions.
- Implement and maintain scalable machine learning and AI engineering frameworks for enterprise-grade applications.
- Build, train, deploy, and optimize ML models at scale, ensuring performance, accuracy, and reliability.
- Develop AI-driven solutions for predictive analytics, automation, and intelligent decision-making.
- Apply GenAI tools and frameworks to deliver modern AI use cases.
- Implement AI algorithms for NLP, computer vision, and recommendation systems.
- Ensure adherence to data governance, security, compliance, and performance best practices.
- Support analytics platform and AI infrastructure deployments where required.
- Contribute to Center of Excellence (CoE) initiatives, standards, and reusable frameworks.
What You Bring to the Table:
- 8–10 years of overall experience in the Data Analytics, AI, and Machine Learning domain.
- Proven experience in Machine Learning Engineering, including: Building, training, and deploying ML models at scale and hands-on experience with TensorFlow, PyTorch, Scikit-learn
- Solid experience in AI Engineering, including: Developing AI-driven solutions for analytics and automation and hands-on exposure to GenAI tools and frameworks
- Implementing AI algorithms for NLP, computer vision, or recommender systems
- Platform knowledge at an intermediate level, with strong conceptual depth in AI/ML systems.
- External certifications in Databricks and/or Microsoft Azure.
You should possess the ability to:
- Design scalable, secure, and high-performing AI/ML solutions for enterprise use cases.
- Apply analytical thinking and structured problem-solving to complex data and AI challenges.
- Adapt quickly to fast-paced environments and evolving AI technologies.
- Lead initiatives within a Center of Excellence, including best practices, standards, and mentoring.
What We Bring to the Table:
- Opportunities to work on enterprise-scale AI, ML, and GenAI initiatives within a Center of Excellence.
- Exposure to advanced analytics platforms, AI frameworks, and data engineering ecosystems.
- Challenging projects involving predictive analytics, automation, and intelligent systems.
- Engagement with cloud-based AI/ML platforms and modern engineering practices.
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Asha Krishnan
Phone: +31 20 369 0609 ; Extn :132
LinkedIn: https://www.linkedin.com/in/asha-krishnan
Skills Required
- 8-10 years of experience in Data Analytics, AI, and Machine Learning
- Proven ML engineering experience building, training, and deploying ML models at scale
- Hands-on experience with TensorFlow, PyTorch, Scikit-learn
- Experience with GenAI tools and AI engineering frameworks
- Experience implementing AI algorithms for NLP, computer vision, or recommender systems
- Intermediate platform knowledge and strong conceptual depth in AI/ML systems
- External certifications in Databricks and/or Microsoft Azure
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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